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Cairo UniversityFaculty of Computers and InformationInformation Technology Department
Improving QoS of Data Transmission over
Wireless Sensor Networks
A Thesis Submitted to the
Faculty of Computers and Information
Cairo University
In Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy
In
Information Technology
BY
Mohamed Hamed Nasr El Din Taha
Under the Supervision of
Prof. Iman Aly SaroitVice Dean of Education and Students
AffairsFaculty of Computers and Information
Cairo University
Prof. Hesham N. ElmahdyInformation Technology Department
Faculty of Computers and InformationCairo University
June2013
بسم هللا الرحمن الرحیم
صدق هللا العظیمطهسورةمن114االية
ii
DeclarationI certify that this work has not been accepted in substance for any academic
degree and is not being concurrently submitted in candidature for any other
degree. Any portions of this thesis for which I am indebted to other sources
are mentioned and explicit references are given.
Student Name: Mohamed Hamed Nasr El Din Taha
Signature:
iii
Acknowledgements
First of all, I thank God for giving the support and providing me with the
patience and guidance which I used in making this work.
I am so grateful to my supervisors Prof. Dr. Imane Aly Saroit and Prof. Dr.
Hesham Elmahdy for providing their valuable time to express their professional
thoughts. I would like to thank them for their help, continuous encouragement, fertile
discussion and valuable suggestions and comments throughout the research and the
thesis work.
This work would not be done without prays, help, support and care of the best
and great person in my life, my mother. Without her, nothing would be done at all. I
would like to thank her for her patience and love. Many thanks for my father who
supports me a lot in my life. I would like to thank my lovely sister for her support.
Finally, I would like to thank my friends who helped me through the PhD and
in the thesis. I pray for God in order to help them through their lives.
iv
Table of ContentsPage
Acknowledgment iii
List of Figures iv
List of Tables ix
List of Abbreviations x
Abstract xv
Chapter 1: Introduction............................................................................ 1
1.1 Problem Definition.................................................................................................... 2
1.2 Research Objectives.................................................................................................. 3
1.3 Contributions............................................................................................................. 3
1.4 Thesis Organization.................................................................................................. 3
Chapter 2: Survey of Wireless Sensor Networks.................................... 5
2.1 Wireless Sensor Network Architecture..................................................................... 5
2.2 Wireless Sensor Network Layers.............................................................................. 8
2.3 Sensor Networks Applications.................................................................................. 12
2.4 WSN Design Objectives........................................................................................... 15
2.5 Challenges of WSN................................................................................................... 18
2.6 Research Areas in Wireless Sensor Networks.......................................................... 23
v
2.7 Routing protocols in Sensor networks...................................................................... 27
2.8 Summary................................................................................................................... 33
Chapter 3: Scheduling Techniques in Wireless Sensor Networks........ 34
3.1 Scheduling in WSN................................................................................................... 34
3.2 End-to-End Packet Delay in WSN............................................................................ 35
3.3 Main Scheduling Concepts in Wireless Sensor Networks........................................ 37
3.4 Summary................................................................................................................... 46
Chapter 4: Proposed Energy Based Scheduling Schema....................... 47
4.1 Main Idea of the Proposed Schema.......................................................................... 48
4.2 Scheme Parameters................................................................................................... 48
4.3 Scheme Equations..................................................................................................... 50
4.4 Priority Queue........................................................................................................... 53
4.5 Integration with routing protocols............................................................................ 53
4.6 WSN Application adaptation.................................................................................... 55
4.7 Properties of proposed Energy Based Scheduling Schema...................................... 57
4.8 Overall proposed schema.......................................................................................... 58
4.9 Summary................................................................................................................... 59
Chapter 5: Simulation of the scheme and results................................... 60
5.1 The Network Simulator (NS-2)................................................................................ 60
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5.2 The Hardware used in the Simulation....................................................................... 64
5.3 Simulations Parameters and environment................................................................. 65
5.4 The Simulations Metrics........................................................................................... 67
5.5 Simulation Results.................................................................................................... 69
5.6 Energy Based Scheduling Scheme with threshold.................................................... 79
5.7 Summary................................................................................................................... 82
Chapter 6: Conclusion and Future Work............................................... 83
6.1 Conclusion................................................................................................................ 83
6.2 Future Works............................................................................................................ 84
Outcome From the thesis.......................................................................... 86
References.................................................................................................. 87
Appendix A - Trace File Field Types....................................................... 95
Appendix B - Sample Awk Scripts........................................................... 98
vii
List of Figures
Figure 2.1 Overview of main sensor node hardware component......................... 6
Figure 2.2 Protocol layers for sensor networks.................................................... 9
Figure 2.3 AODV route discovery....................................................................... 28
Figure 2.4 AODV RREQ packet.......................................................................... 29
Figure 2.5 AODV RREP packet........................................................................... 30
Figure 2.6 AODV RERR packet.......................................................................... 30
Figure 2.7 AODV Hello packets.......................................................................... 31
Figure 3.1 Scheduler function model................................................................... 34
Figure 3.2 Classifications of Packet scheduling techniques................................. 38
Figure 4.1 Scheduling Schema in WSN architecture........................................... 56
Figure 4.2 Packet Energy consumption vs. the threshold..................................... 57
Figure 5.1 Architecture of the WSN node in NS-2.............................................. 63
Figure 5.2 The position of the sink node in the simulated WSN.......................... 66
Figure 5.3 Network average Energy Level across Network life time.................. 70
Figure 5.4 Network Energy consumption vs. Packet Delivery Ratio................... 71
Figure 5.5 Fairness Index..................................................................................... 73
Figure 5.6 Network average Energy Level across Network life time.................. 74
Figure 5.7 Average Network Energy consumption vs. Packet Delivery Ratio in
DSDV..................................................................................................
75
Figure 5.8 Fairness Index of DSDV vs. the AODV with proposed schema........ 76
Figure 5.9 Network average Energy Level across Network life time.................. 77
viii
Figure 5.10 Average Network Energy consumption vs. Packet Delivery Ratio in
DSR
78
Figure 5.11 Fairness Index of DSDV vs. the AODV with proposed schema........ 79
Figure 5.12 Fairness Index the Energy Based Scheduling Schema before and
after applying the threshold.................................................................
81
Figure 5.13 Dropping Probability vs. the distance from the sink node.................. 81
ix
List of Tables
Table 3.1 Packet priorities when different VMS policies are used………....…. 43
Table 4.1 Amount of reserved bits (unused bits)…………………………….... 55
Table 5.1 Simulation Parameters…………………………………………….... 65
x
List of Abbreviations
AODV Ad hoc On Demand Distance Vector
CBR Constant Bit Rate
DSDV Destination-Sequenced Distance-Vector
DSR Dynamic Source Routing
DVM Dynamic Velocity Monotonic Scheduling
EB-AODV Energy Based Scheduler with AODV
EETD End to End Estimation of Transmission Delay
ETD Estimation of Transmission Delay
FIFO First In First Out
JiTS Just-in-Time Schedules
LFF Lagging Flow First
IFq Interface Queue
LL Link Layer Object
MAC Medium Access Control
NAM Network Animator
NS-2 Network Simulator-2
OTCL Object Oriented Extension Of Tcl
PD Packet Deadline
PEC Packet Energy Consumption During Transmission
PEP Packet Energy Path Level
PS Packet Size
PSP Packet Sending Priority
QoS Quality of Service
RAM Random Access Memory
RERR Route Error Message
xi
RREP Route Replay Message
RREQ Route Request Message
RREP-ACK Route Replay Message - Acknowledgment
SVM Static Velocity Monotonic Scheduling
TCL Tool Command Language
TTL Time to Live
WSN Wireless Sensor Network
xv
Abstract
Wireless Sensor Networks (WSNs) consist of sensor nodes that are spatially
distributed. These sensor nodes are connected to each other through wireless
technology. They are an important emerging technology that will revolutionize
sensing for a wide range of military, scientific, industrial and civilian
applications. In many WSN applications, the sensor nodes are deployed in an
ad hoc style without careful any preplanning and engineering. Once deployed,
the sensor nodes must have the ability to autonomously organize themselves
into a wireless communication network.
New packet scheduling schemes have been developed for real-time data
communication. These schemes work on prioritizing packets according to their
deadlines. Packet prioritizing cannot support real time applications or assure
network lifetime. In extreme traffic environments, large queues may lead to
packet delay and packet dropping. Packet dropping leads to energy loss, as a
packet could have consumed high energy in order to be delivered to its
destination.
The continuous decrease in the size and cost of sensors has motivated
intensive research addressing the potential of collaboration among sensors in
data. Current research on routing and scheduling in wireless sensor networks
focused on energy aware protocols to maximize the lifetime of the network.
These researches are scalable to accommodate a large number of sensor nodes.
In addition, they are tolerant to sensor damage and battery exhaustion. Sensor
networks are deployed to gather information for later analysis, monitoring or
tracking of phenomena in real-time.
In WSNs, transmitted packets are queued at intermediate nodes. Each node
schedules the queued packets by assigning priorities to each packet. Priorities
are assigned to packets according to their deadlines. This method in packet
xvi
prioritization does not take into consideration either the network life time or
energy consumption. Besides, it may lead to dropping high energy valuable
packets. In many applications, WSN lifetime is considered a very critical issue,
while setting up the network.
In this thesis, a new scheduling scheme, named Energy Based Scheduling
scheme is introduced. In this scheme, packets are not only prioritized according
to their deadlines but also according to some energy measures related to the
network, that are obtained from the network nodes and are used in packet
prioritization. The proposed scheme is integrated with the AODV routing
protocol. The unused bits in the AODV packets are used by the proposed
scheme in assigning sending priorities to each packet in the network. Through
this thesis, the proposed scheduling scheme is compared with the Basic Priority
Scheduling scheme, using NS-2. Comparisons are done according the network
life time, energy consumption and the fairness index measure. The results
prove that the Energy Based scheduling scheme increase the network life time
and decrease the energy consumption for the goodput packets. On the other
hand, the fairness index was affected.
Keywords: Wireless Sensor Networks, scheduling scheme, AODV, Basic
Priority scheduling scheme, NS-2
1
Chapter 1
Introduction
Wireless networks, like wireless mobile ad-hoc networks and Wireless
Sensor Networks (WSNs) have played a great important role in a wide range of
applications. In the 21st century, they have been identified as one of the most
important technologies. WSNs are a rapidly emerging technology which will
have a strong impact on research and will become an integral part of life in the
near future. The huge application space of WSNs covers health care,
surveillance, military, environment monitoring and many more. Because of
their great usage applications, they have attracted considerable research interest
in recent years. WSNs support monitoring and controlling of physical
environments from remote locations with better accuracy [1].
Sensor networks are dense wireless networks of small and low-cost sensors.
They are composed of a large number of sensors deployed randomly in an ad-
hoc manner in the area/target to be monitored. Sensors collect and disseminate
environmental data. Each sensor has limited battery energy supply,
transmission radius and sensing capability. The random deployments of
sensors don’t require be engineering or predetermining. This allows fast
random deployment in inaccessible terrains or disaster relief operations [2]. On
the other hand, random deployment requires that sensor network protocols and
algorithms must possess self-organizing capabilities. They support monitoring
and controlling of physical environments from remote locations with better
accuracy [3].
In wireless sensor networks, energy sources provided for sensors are usually
battery power. It has not yet reached the stage for sensors to operate for a long
time without recharging. The energy conservation is the most critical issue
because of the weight and size limitations of sensor nodes [4].
2
Since sensors are often purposed to work in remote or hostile environment,
such as a battlefield or desert, it is undesirable or impossible to recharge or
replace the battery power of all the sensors.
WSNs can be deployed in the places where the wired sensor system cannot
be deployed. These places are in the chemical environments that are
inaccessible by humans. They are used in ordet to facilitate monitoring and
controlling of physical environments from remote locations with better
accuracy [5].
1.1 Problem DefinitionSensors are often purposed to work in remote or hostile environment, such
as a battlefield or desert. So, it is unwanted or impossible to recharge or replace
the battery power of all the sensors [6].
WSNs contain a lot of constrains, such as energy limitation, decentralized
collaboration, and fault tolerance. These constraints cause many unresolved
design and implementation problems, so measurements are virtually
impossible. However, long system lifetime is expected by many monitoring
applications. The system lifetime, that is measured by the time until all nodes
have been drained out of their battery power or the network no longer provides
an acceptable event detection ratio, directly affects network usefulness [4, 7].
The most energy consuming operation is data transmission and reception.
Control messages and sensing and processing operations also contribute to the
energy consumption [8]. In order to minimize the consumed energy, dropping
packets should not be only according to the deadline but also according to the
packet energy consumption. So, the scheduling needs to consider the queuing
delay and packet energy consumption, in order to achieve better network QoS
and improve the WSN lifetime [9, 10].
3
1.2 Research ObjectivesThe objective of this thesis is to introduce a new scheduling schema. Most
of WSN energy consumption is due to the packet transmission. The new
schema should have the ability to prioritize packets according to energy
consumption and deadline, besides improving the network quality of service.
In WSN, packets are buffer in each node on the path from source to
destination. As each node has a finite buffer size, packets are dropped and
transmitted in order to keep the queue ready for new packets. Dropping and
transmitting packets is done according to many constraints.
The process of managing the packets in each node queue is called
scheduling. Existing Scheduling algorithms are according to deadline or the
technique of first come first served. Energy consumption by the packets during
the transmission and reception process is not considered in any scheduling
algorithm.
1.3 ContributionsIn this thesis, we develop the Energy Based Scheduling schema for Wireless
Sensor Networks. It offers a significant improvement in the network lifetime
and QoS. It reduces the energy consumption and a packet delay for remote
nodes from the destination. Both data and control packets are treated in the
same manner, according to energy consumption and packet deadline.
1.4 Thesis OrganizationThe rest of the thesis is organized as follows:
Chapter 2 presents an introduction to wireless sensor networks, including
network architecture, layers, Applications and challenges. This introduction
includes the sensor hardware component and the types of WSN architectures.
In addition, the main types of routing protocol are mentioned including Pro-
4
active (Table-Driven) routing and Reactive (On Demand) Routing Protocols.
The main routing protocols for these types were briefly discussed.
In chapter 3, we present a brief review of Scheduling techniques in Wireless
Sensor networks and the types of delay in WSN. This review includes the
main types of the scheduling techniques which they depend on in packet
scheduling.
Through chapter 4, the proposed energy based scheduling schema is
introduced. The equations used in the proposed schema are discussed. Besides,
the integration of the proposed schema with AODV routing protocol has been
discussed.
The simulation and results when comparing the proposed energy schema, is
introduced in chapter 5. In this chapter, a comparison is done between the
proposed energy schema with AODV and the basic priority scheduling schema
with AODV, DSR and DSDV.
Finally, chapter 6 concludes the thesis and presents a future work of it.
5
Chapter 2
Survey on Wireless Sensor Networks
Advancements in the area of wireless communication technologies are
undergoing rapidly. The last years have experienced a huge growth in
research in the area of wireless sensor networks (WSNs). In WSNs,
communication is established with the help of distributed sensor nodes are
used to sense specific information [12]. WSNs consist of individual nodes
that are able to react with their environment by sensing, monitoring or
controlling physical parameters. WSNs are powerful because of its ability to
support a lot of different real-world applications. In a WSN, each sensor
node has the ability to independently perform some processing and sensing
tasks [1]. The position of sensor nodes doesn’t need to be engineered or pre-
determined. This means that wireless sensor network protocols and
algorithms must be able to possess self-organizing capabilities.
In this chapter, we will introduce wireless sensor network architecture,
applications, protocols and challenges.
2.1 Wireless Sensor Network ArchitectureA WSN is a network consisting of many sensor nodes with sensing,
wireless communications and computing capabilities. These sensor nodes
are dispersed in an unattended environment (i.e. sensing field) to sense the
physical world. The sensed data can be gathered by a few sink nodes which
have accesses to infrastructure networks like the Internet [13].
The hardware resources, which are available on micro-sensor nodes, are
significantly more limited than other wireless devices such as PDAs or
laptops. This limitation is driven by cost and size considerations. The
challenge is how to make balance the application requirements and the
limited available resources. Reducing the consumed energy is often the
primary target; since the transmission is one of the most costly operations
6
(transmitting 1 byte 100 meters consumes similar energy as processing
several thousand instructions) [10, 14].
The concept of wireless sensor networks is based on a simple equation
[15]
Sensing + CPU + Radio = Thousands of potential applications
2.1.1 The Sensor node ArchitectureA basic sensor node comprises five main components (Figure 2.1) [16]:
Controller: A controller works on processing all the relevant data,
capable of executing arbitrary code.
Memory: It is used to store programs and intermediate data; usually,
different types of memory are used for programs and data.
Sensors and actuators: They are actual interface to the physical world:
devices which can be able to observe or control physical parameters of
the environment.
Communication: In order to turn nodes into a network, a device
requires sending and receiving information over a wireless channel.
Power supply: As usually no tethered power supply is available. Some
forms of batteries are necessary to provide energy. Sometimes, some
form of recharging by obtaining energy from the environment is
available as well (e.g. solar cells).
Figure 2.1 Overview of main sensor node hardware component
ControllerSensors /ActuatorsCommunication
device
Power supply
Memory
7
2.1.2 Wireless Sensor Networks ArchitecturesWSNs are considered application specific. A sensor network is usually
deployed for a specific application. Therefore, it has some different
characteristics. According to different criteria, WSNs are classified into
different categories [17].
Static and Mobile Network. According to the mobility of sensor
nodes, a sensor network can be static or mobile. In a static sensor
network, all sensor nodes are static without movement, which is the
case for many applications. However, some sensor applications
require mobile nodes to accomplish a sensing task [18, 19].
Deterministic and Nondeterministic Network. According to the
deployment of sensor nodes, a sensor network can be deterministic or
nondeterministic. In a deterministic sensor network, the positions of
sensor nodes are preplanned and are fixed once deployed. It is difficult
to deploy sensor nodes in a preplanned manner because of the harsh or
hostile environments. Instead, sensor nodes are randomly deployed
without preplanning and engineering. Obviously, nondeterministic
networks are more scalable and flexible, but require higher control
complexity [20, 21].
Static - Sink and Mobile - Sink Network. A data sink in a sensor
network can be static or mobile node. In a static - sink network, the
sinks are static with a fixed position located close to or inside a
sensing region. All sensor nodes send their sensed data to the sink(s).
In a mobile - sink network, the sink(s) move around in the sensing
region to collect data from sensor nodes, which can balance the traffic
load of sensor nodes and alleviate the hotspot effect in the network
[22, 23].
Single - Sink and Multisink Network. A sensor network can have a
single sink or multiple sinks. In a single - sink network, there is only
8
one sink located close to or inside the sensing region. All sensor nodes
send their sensed data to this sink. In a multisink network, there may
be several sinks located in different positions close to or inside the
sensing region [24].
Single - Hop and Multihop Network. According to the number of
hops between a sensor node and the data sink, a sensor network can be
classified into single - hop or multihop. In a single - hop network, all
sensor nodes transmit their sensed data directly to the sink, which
makes network control simpler to implement. Multihop networks have
a wider range of applications at the cost of higher control complexity
[25].
Self - Reconfigurable and Non - Self - Configurable Network.
According to the configurability of sensor nodes, a sensor network can
be self - configurable or non - self - configurable. In a non - self -
configurable network, sensor nodes have no ability to organize
themselves into a network. Instead, they have to rely on a central
controller to control each sensor node and collect information from
them. A network with such self - configurability is suitable for large -
scale networks to perform complicated sensing tasks [26].
Homogeneous and Heterogeneous Network. According to whether
sensor nodes have the same capabilities, a sensor network can be
homogeneous or heterogeneous. In a homogeneous network, all sensor
nodes have the same capabilities in terms of energy, computation, and
storage. In contrast, a heterogeneous network has some sophisticated
sensor nodes that are equipped with more processing and
communicating capabilities than normal sensor nodes [27].
2.2 Wireless Sensor Networks LayersThe protocol layers for WSNs consists of five protocol layers, the
physical layer, data link layer, network layer, transport layer, and
9
application layer, as shown in Figure 2.2. The protocol layers can be divided
into a group of management planes across each layer. Each layer includes
power, connection, and task management planes. The power management
plane has the responsibility for managing the power level of a sensor node
for, processing, sensing, transmission and reception, which can be
implemented by employing efficient power management mechanisms at
different protocol layers [28]. The connection management plane is
responsible for the configuration and reconfiguration of sensor nodes to
establish and maintain the connectivity of a network in the case of node
deployment and topology change due to node addition, node failure, node
movement. The task management plane is responsible for task distribution
among sensor nodes in a sensing region in order to improve energy
efficiency and prolong network lifetime [29].
Figure 2.2 Protocol layers for sensor networks
2.2.1 Physical layerThe responsibilities of the Physical Layer are carrier frequency
generation, frequency selection, signal detection, modulation and
10
encryption. Its first priority is energy minimization and secondary concerns
are the same as those of other wireless networks. This task is carried out by
devices called transceivers. So, it should deal with various related issues,
like transmission medium and frequency selection, carrier frequency
generation, signal modulation and detection, and data encryption.
2.2.2 Data Link LayerThe data link layer has the responsibility of multiplexing of data frame
detection, data streams, medium access and error control. It has the task of
ensuring a reliable communications link between neighboring nodes, which
in the case of WSNs means between nodes in radio range.
2.2.2.1 Medium Access Control (MAC) protocolsMedium Access Control (MAC) protocols are the first and most
important protocol layer above the Physical Layer. Medium access was and
still one of the most active research areas for WSNs. MAC is one of the
critical issues in the design of wireless sensor networks (WSNs) The main
functions of a MAC protocol for WSNs are the coordination and scheduling
of transmissions between the competing nodes. The design of MAC
protocols for WSNs must take in consideration the characteristics of these
networks such as the node mobility, the lack of any central coordination, the
unreliability of the wireless medium, the problems of hidden and exposed
nodes and the energy constrained problem.
Modified versions of the IEEE 802.11 MAC layer protocol are often used
by sensor network platforms. Since IEEE 802.11 is the most deployed
wireless MAC protocol, it has been chosen as the main MAC protocol in our
thesis.
The 802.11 MAC layer specifications specifies two kinds of access
methodologies as follows.
1. Point Coordination Function (PCF): It is usually used for real
time data transmission with priorities in infrastructure networks. This
11
is a contention free access protocol; PCF is not used in Ad hoc
networks.
2. Distributed Coordination Function (DCF): Probably, all Ad hoc
networks (including sensor networks) use DCF as the access
methodology. This is a contention based access protocol. This section
describes the features of DCF.
2.2.3 Network LayerThe network layer is surely the area with the most active research
interest. Network layer mainly deal with determining the route from source
to destination and manage traffic problems. Generally, network layer is
responsible for end-to-end packet delivery, whereas the data link layer is
responsible for node-to-node (hop-by-hop) packet delivery [21]. Routing
protocols in WSN can be categorized as follows:
Data-Centric: Data are spreaded between sensors without the need
for global unique ID. It depends on the naming of desired data.
Hierarchical: Sensors are controlled by a sensor (cluster-head) to
aggregate data. Cluster-head is either a special (more powerful) node
or an elected sensor among each cluster.
Location-based: These protocols are location-aware; by utilizing a
Global Positioning System (GPS). The ability to find the location
makes it easier to route data to single and specific region instead of
broadcasting traffic to all regions.
Quality of Service based: Protocols which ensure some QoS
requirements such as minimum cost path, minimizing energy
consumption, low throughput and delay.
2.2.4 Transport LayerIt is responsible for packet transmission and reception. In other words, it
is responsible for reliable end to end data delivery between sensor nodes and
the sink(s). Routing protocols are handled in this layer. Normal transport
protocols developed for wireless or wired communication does not address
12
WSN resource constrains [16]. Some consideration must be taken while
developing transport protocols specific for WSN:-
Reliability for both ways of communications; sink-to-sensors and
sensor-to sink.
A good Congestion Control mechanisms increases network efficiency
and save power.
Self-configuration approaches to adapt to frequent changes in
network topology.
Should be energy-aware.
Data-centric.
2.2.5 Application LayerMany WSNs’ applications heavily rely on coordinated services such as
localization, time synchronization, and in-network data processing to
collaboratively process data. Normal transport protocols developed for
wired or wireless communication does not address WSN resource
constrains. Although many sensor network applications have been proposed,
their corresponding application - layer protocols still need to be developed
[28].
2.3 Sensor Networks ApplicationsWSNs find a diversity of applications in both the civilian population and
the military a worldwide. They can be used in various applications such as
intelligent agriculture, medical health care, environment monitoring and
protection, and military battlefield surveillance. In many WSN applications,
individual nodes in the network cannot easily be connected to a wired power
supply, so they have to rely on onboard batteries [30]. This means that,
energy efficiency of any proposed solution is a very important issue, if the
power supply is an issue. WSNs can be divided into two types,
homogeneous and heterogeneous [30]. In heterogeneous networks, there are
different types of sensors. They perform multiple operations simultaneously.
While in homogeneous, each node has an identical function and performs
13
the same task. In this section, some WSNs applications will be discussed
[27].
2.3.1 Environment applicationsEnvironmental monitoring can be used for animal tracking, forest
surveillance, flood detection, and weather forecasting. It is one of the
primary applications of wireless sensor networks. The advantages of WSNs
are the long-term, unattended, wirefree operation of sensors close to the
objects that have to be observed. WSNs can be used in gaining an
understanding of the number of plant and animal species that live in a given
habitat [31].
2.3.2 Military applicationsThe initial wireless sensor network is used in the military applications.
Since sensor nodes are low-cost, destruction of some nodes by hostile
actions in the battlefields may not affect a military operation. Military
applications are very closely related to the concept of wireless sensor
networks. WSNs are used in covering areas of interest extents from
information collection to battlefield surveillance, enemy tracking or target
classification [31].
Battlefield Monitoring: Sensors are deployed in a battlefield to
monitor the presence of forces and vehicles, and track their
movements, enabling close surveillance of opposing forces.
Object Protection: Sensor nodes are deployed around sensitive
objects, for example, atomic plants, strategic bridges, oil and
communication centers, gas pipelines, and military headquarters, for
protection purpose.
Intelligent Guiding: Sensors can be mounted on unmanned robotic
vehicles, tanks, submarines, missiles, fighter planes, or torpedoes to
guide them around obstacles to their targets and lead them to
14
coordinate with one another to accomplish more effective attacks or
defenses.
Remote Sensing: Sensors could be deployed for remote sensing of
biological, nuclear and chemical weapons, detection of potential
terrorist attacks, and reconnaissance.
2.3.3 Health Care ApplicationsWSNs can be used to monitor and track elders and patients for health
care purposes, which can significantly relieve the severe shortage of health
care personnel and reduce the health care expenditures in the current health
care systems [32]
Behavior Monitoring: Sensors can be deployed in a patient’s home
to monitor the behaviors of the patient. For example, it can alert
doctors when the patient falls and requires immediate medical
attention. It can monitor what a patient is doing and provide
reminders or instructions over a television or radio.
Medical Monitoring: Sensors can be integrated into a wireless body
area network to monitor vital signs, environmental parameters, and
geographical locations. Besides, they allow long term, noninvasive,
and ambulatory monitoring of patients or elderly people with
instantaneous alerts to health care personal in case of emergency,
immediate reports to users about their current health statuses, and real
- time updates of users’ medical records.
2.3.4 Industrial Process ControlIn industry, WSNs can be used to monitor manufacturing processes or the
condition of manufacturing equipment. For example, wireless sensors can be
instrumented to production and assembly lines. So, they can be able to
monitor and control production processes. Chemical plants or oil refiners
can use sensors to monitor the condition of their miles of pipelines. Tiny
sensors can be embedded into the regions of a machine that are inaccessible
15
by humans to monitor the condition of the machine and alert for any failure
[33].
2.3.5 Security and SurveillanceWSNs can be used in many security and surveillance applications. For
example, acoustic, video and other kinds of sensors can be deployed in
buildings, airports, subways and other critical infrastructure. Also, sensors
can be used in nuclear power plants or communication centers to identify
and track intruders, and provide timely alarms and protection from potential
attacks [32].
2.3.6 Home IntelligenceWSNs can be used to provide more convenient and intelligent living
environments for human beings [32].
Smart Home. Wireless sensors can be embedded into a home and
connected to form an autonomous home network. For example, a
smart refrigerator connected to a smart stove or microwave oven can
prepare a menu based on the inventory of the refrigerator. Then, it
sends relevant cooking parameters to the smart stove or microwave
oven, which will set the desired temperature and time for cooking.
The contents and schedules of TV, VCR, DVD, or CD players can be
monitored and controlled remotely to meet the different requirements
of family members.
Remote Metering. Wireless sensors can be used to remotely read
utility meters in a home like water, gas, or electricity and then sends
the readings to a remote center through wireless communication.
2.4 WSN Design ObjectivesSensor Networks characteristics and requirements for different
applications have a decisive impact on the network design objectives in
terms of network capabilities and network performance. WSN design should
follow some aspects in order to achieve its goal. They are:
16
Small Node Size. One of the primary design objectives of sensor
networks is to reduce the node size. Sensor nodes are usually
deployed in a harsh or hostile environment in huge numbers.
Reducing node size can facilitate node deployment, and also reduce
the cost and power consumption of sensor nodes.
Low Node Cost. Node cost reduction is another primary design
objective of sensor networks. Since sensor nodes are usually
deployed in a harsh or hostile environment in large numbers and
cannot be reused, it is important to reduce the cost of sensor nodes so
that the cost of the whole network is reduced.
Low Power Consumption. Reducing power consumption is the most
important objective in the design of a sensor network. Since, the
sensor nodes are powered by battery and it is often very difficult or
even impossible to change or recharge their batteries. It is crucial to
decrease the power consumption of sensor nodes in order to increase
the lifetime of the sensor nodes, in addion to the whole network.
Self - Configurability. In sensor networks, sensor nodes are usually
deployed in a region of interest without careful planning and
engineering. Once deployed, sensor nodes should be able to
autonomously organize themselves into a communication network
and reconfigure their connectivity in the event of topology changes
and node failures.
Scalability. In WSNs, the number of nodes may be on the order of
tens, hundreds, or thousands. Thus, network protocols designed for
sensor networks must be scalable to different network sizes.
Adaptability. In sensor networks, any node may fail, join, or move,
which would result in changes in node density and network topology.
Thus, network protocols which are designed for sensor networks
should be adaptive to such density and topology changes.
17
Reliability. For many sensor network applications, it is required that
data be reliably delivered over noisy, error - prone, and time - varying
wireless channels. To meet this requirement, network protocols
designed for sensor networks must have the ability to provide error
control and correction mechanisms to ensure reliable data delivery.
Fault Tolerance. Sensor nodes are apt to failures due to harsh
deployment environments and unattended operations. So, sensor
nodes must be able to be fault tolerant and have the abilities of self -
testing, self -repairing, self - calibrating and self - recovering.
Security. In many military applications, sensor nodes are deployed in
a hostile environment and thus are vulnerable to adversaries. In such
situations, a sensor network should introduce effective security
mechanisms to prevent the data information in the network or a
sensor node from unauthorized access or malicious attacks.
Channel Utilization. Sensor networks have limited bandwidth
resources. Thus, communication protocols designed for sensor
networks should efficiently make use of the bandwidth to improve
channel utilization.
QoS Support. In sensor networks, different applications might have
different QoS requirements in terms of delivery latency and packet
loss. For example, some applications, for example, fi re monitoring,
are delay sensitive and thus require timely data delivery. Some
applications, for example, data collection for scientific exploration,
are delay tolerant but cannot stand packet loss. Thus, the design of
network protocol should consider the QoS requirements of specific
applications.
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2.5 Challenges of WSNHandling a wide range of application types would hardly be possible
with any single realization of a WSN [34].
2.5.1 System ArchitectureThere is no unified system and networking architecture that is stable and
mature enough to build different applications on top. Most of the
applications and research prototypes are vertically integrated in order to
maximize performance.
2.5.2 Wireless ConnectivityWireless communication in indoor Environments is still quite
unpredictable using low-power consumption RF transceivers, in particular in
clutter environments common inside buildings, with many interfering
electromagnetic fields, such as the one produced by elevators, machinery
and computers, among others.
2.5.3 ProgrammabilitySome form of network re-programmability is desirable; doing so in
energy and communication conservative form remains a challenge. Nodes
should be programmable, and their programming must be changeable during
operation, when new tasks become important. This means that a fixed way
of information processing is not sufficient.
2.5.4 AdaptationThe network operation should adapt itself to application requirement
changes, time-varying wireless channels, and variations of the network
topology. For instance, the group of application requirements may change
dynamically and the communication protocol must adapt its parameters to
satisfy the specific requests of the control actions.
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2.5.5 Energy ConsumptionSensors nodes are battery powered nodes and thus have very limited
energy capacity. Energy consumption is a central design consideration for
wireless sensor networks whether they are powered using batteries or energy
harvesters. The energy constraint will not be solved soon due to slow
progress in developing battery capacity [30]. In many scenarios, nodes will
have to rely on a limited supply of energy. Replacing the energy sources in
the field is usually not practicable or a visible solution. Surveillance nature
of many sensor network applications requires long lifetime. So, it must be a
very important research topic to provide a form of energy-efficient
surveillance service for a geographic area.
The energy consumed for transferring one bit of data to a receiver at 100
m away is equal to that needed to execute 3,000 instructions. The ratio of
energy consumption for communicating 1 bit over the wireless medium to
that for processing the same bit could be in the range of 1,000 – 10,000.
Furthermore, the energy consumed for transmission dominates the total
energy consumed for communication and the required transmission power
grows exponentially with the increase of transmission distance. Therefore, it
is desired to reduce the amount of traffic and transmission distance in order
to increase energy savings and prolong network lifetime [30].
The precise definition of lifetime depends on the requirement of
application at hand. The main limiting factor for the lifetime of a sensor
network is the energy supply. Each sensor node should be designed to
manage its local supply of energy in order to maximize total network
lifetime. The node minimum lifetime is more important than the average
node lifetime [35].
There direct trade-offs between the lifetime of a network and quality of
service. As, investing more energy can increase quality but decrease
lifetime. In a wireless sensor node the radio consumes a vast majority of the
system energy. This power consumption can be reduced through decreasing
the transmission output power or through decreasing the radio duty cycle.
Both of these alternatives involve sacrificing other system metrics.
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2.5.6 Quality of ServiceQuality of service (QoS) is an important factor in networking, but it is
also a significant challenge. The QoS is one of the most important
challenges that face WSN. More energy is required to achieve better QoS.
Therefore, WSN lifetime is affected. Providing QoS guarantees have
become even more challenging when you add the complexities of wireless
and mobile networks [17].
2.5.6.1 Definition of Quality of ServiceQoS is the ability to provide different priorities to different applications,
users, or data flows, or to guarantee a certain level of performance to a data
flow. QoS guarantees are important if the network capacity is a limited
resource. Due to the limitation of network resources especially in wireless
networks, real time traffic need to be given higher priority to ensure that
arrival to the destination on time.
2.5.6.2 Quality of Service parametersQoS parameters differ from application to application. In sensor
networks, battery life and energy conservation would be the prime QoS
parameters. The QoS parameter considered here is aimed to real time
applications. However, maximizing QoS and minimizing energy
consumption are in most cases conflicting requirements [17].
2.5.6.3 Quality of Service in different layers Physical layer: It means the quality in terms of transmission
performance. Power control is used both to ensure the quality of
reception and to optimize the capacity. It seeks to avoid the
interference with other networks or natural sources of radiation.
Data Link layer: The scheduling of medium access and the
sequence of packets to be sent is changed to supply the QoS
requirements. These changes may be achieved by packet reordering
and by priority control and admission policies. It is possible to adjust
21
the amount of control packets sent to increase the QoS of a data
packet. Current proposed MAC protocols in WSN concerns mainly
about power conserving. They don’t support real QoS due to the
tradeoffs between energy efficiency and QoS capability. QoS
implemented in MAC layer is also important. It could provide high
probability of access with low delay when stations with higher user
priority want to access the wireless medium [36].
Network Layer: It mainly deals with determining the route from
source to destination and manages traffic problems. Some routing
protocols in WSN are developed to ensure some QoS requirements
such as minimum cost path; in term of energy for example, low
throughput and delay. Similar to the link layer, it is possible to use
packet prioritization.
Application Layer: QoS may interpret in two different prospective.
One prospective defines QoS as quality perceived by the user or
application (subjective). The other is defining QoS in respect to
network
2.5.6.4 Models of Quality of ServiceQoS model are defined into two types. They are Integrated Service (IntServ)
and Differentiated Services (DiffServ) [38].
IntServ: provides QoS to individual applications or flows. Resource
Reservation Protocol is used to provide a circuit switched service in
packet switched network. IntServ decides if the desired service could
be provided with the current available network resource. The
scalability problem is the main drawback of IntServ. It caused by the
need of storing every flow state in the routes.
DiffServ: provides QoS to large classes of data or aggregated traffic.
Routers are divided into two types: edge routers and core routers.
22
Edge routers are at the boundary of the networks. In edge routers,
traffic will be classified, conditioned and assigned to different
behavior aggregate when it traverse between different networks. Core
routers forward packets based on this ToS field. In addition, core
routes also need to follow the per-hope behavior which takes charge
of scheduling of packets.
2.5.6.5 Challenge of QoS in WSNWSNs differ from the traditional wired networks. Due to bandwidth,
memory and processor limitations, QoS in WSN is a challenging task.
WSNs have certain unique characteristics which cause difficulties for
providing QoS in such networks [39]. These characteristics are:-
Dynamically varying network topology
In a WSN, mobility problem can also exist if the sensor nodes are
mobile in the given application. When nodes are mobile, network
topology is changing dynamically. The route which is already set up
with required QoS could not satisfy QoS anymore if one of the nodes
on this established route moves. A node could move to an area with
more interference to it.
Limited resource availability
WSN life nature is limited because of the fact that most nodes
operate on unchangeable power source like battery; another reason is
the ease of node damage. The data rate is so limited for wireless
links if we compared it with the data rate available in wired network.
The basic characteristics of the wireless channel like fading, noise,
and shared data rate between neighbor nodes will also degrade the
wireless data rate. The actual radio data rate becomes much smaller.
As a result, it is very hard for a wireless network to provide too high
data rate which could be provided by the wired network. It also
brings problem of cooperation between wireless network and wired
network.
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Lack of precise state information
Because of the dynamic characteristic, information of nodes
transmitted to other nodes may change right after this information is
transmitted to its neighbors.
Application diversity
WSN consider being application specific rather than general purpose.
They carry only the software and hardware that is needed for the
application. The vast number of applications in WSN offers different
QoS requirements.
Data correlation
Data, which is collected by a sensor node, tends to be correlated to
the data collected by its neighbors, thus it may be dropped or
submitted to fusion or preprocessing in order to decrease bandwidth
utilization.
2.6 Research Areas in Wireless Sensor NetworksWireless sensor network faces a lot of problems. These problems appear
from the nature of the WSN [39]. Through this section, we focus on the
most important problems in wireless sensor networks.
2.6.1 Localization in WSNIn wireless sensor networks, localization is identified as the process of
determining the geographical positions of sensors. In other words, it is
defined as an algorithm that finds the Euclidean position for some or all of
the nodes in the network. Only some of the sensors in the networks have
prior knowledge about their geographical positions. In many applications of
wireless sensor networks, valuable location information of sensor nodes is
critical to the success of the applications. Most of the collected data from
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sensors are only meaningful when they are coupled with the location
information of the corresponding sensors [40].
For example, consider an application of habitat monitoring. Thousands of
sensors are dropped in the target region of a tropical rain-forest by an
aeroplane. sensing devices are attached with nodes to monitor the changes
of temperature and humidity of the environment.
2.6.2 Routing in WSNSensor networks can be considered a special class of ad hoc networks.
Routing for traditional ad hoc networks is considered a well-researched area
and it is possible to adapt protocols developed there to sensor network
operation. For some applications, messages should arrive at a destination by
a deadline. Due to the high degree of uncertainty in WSN it is difficult to
develop routing algorithms with any guarantees. However, several
characteristics of sensor networks make such protocols poorly suited for
them. These characteristics include [41]:
Data dissemination model of the sensor networks is far from the
view of the traditional wireless ad hoc networks where mostly the
communication is from one source to one destination;
Data-centric operation where communication is directed to sensors
that satisfy a query attributes differs from the IP-centric view of ad
hoc networks
The emphasis of ad hoc networks is on mobility, many sensor
networks are static.
Sensor network nodes are more energy constrained than ad hoc
nodes, and are not rechargeable. Because of these reasons, several
new routing protocols have been proposed for sensor networks.
There are two types of routing protocols which are reactive and
proactive. In reactive routing protocols, the routes are created only when
source wants to send data to destination whereas proactive routing protocols
are table driven. Reactive routing protocol uses traditional routing tables.
25
One entry per destination and sequence numbers are used to determine
whether routing information is up-to-date and to prevent routing loops.
2.6.2.1 Pro-active (Table-Driven) routingProactive routing protocols preserve routes to all destinations, regardless
of whether or not these routes are needed. In order to preserve correct route
information, a node must periodically send control messages. Therefore,
proactive routing protocols may waste bandwidth since control messages are
sent out unnecessarily when there is no data traffic. The main advantage of
this category of protocols is that nodes can quickly obtain route information
and quickly establish a session [42].
2.6.2.2 Reactive (On Demand) Routing ProtocolsReactive routing protocols have the ability to dramatically reduce routing
overhead because they do not need to search for and maintain the routes on
which there is no data traffic. On demand routing protocols execute the path
finding process and exchange routing information only when there is a
requirement by the station when it want to initialize a transmission to some
destination. By using the method of on demand routing, the routing load is
decreased a lot. This property is very appealing in the resource-limited
environment [43].
2.6.2.2 Hybrid Routing ProtocolsThe advantages of proactive and of reactive routing are combined in this
type of routing protocols. The routing is initially established with some
proactively prospected routes and then serves the demand from additionally
activated nodes through reactive flooding.
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2.6.3 MAC protocols in Wireless Sensor networksAs in all shared-medium networks, medium access control (MAC) is an
important technique which enables the successful operation of the network.
A MAC protocol specifies how nodes in a wireless sensor network
coordinate their communication over a shared communication channel.
A significant amount of energy is consumed by the sensor node’s radio.
Great research has been done on the design of low power electronic devices
in order to reduce energy consumption of these sensor nodes. Due to the
hardware limitations, energy efficiency can be achieved through the design
of energy efficient communication protocols. MAC is an important
technique which ensures the successful operation of the network. One
fundamental task of the MAC protocol is to avoid collisions from interfering
nodes.
MAC protocols for the WSN must achieve two objectives. The first
objective is the creation of the sensor network. A large number of sensor
nodes are deployed and the MAC scheme should be responsible for
establishing the communication links between the sensor nodes. The second
objective is to achieve better fairness index value. This could be done by
sharing the communication medium fairly and efficiently.
The network topology changes over time as well due to many reasons. A
good MAC protocol should be able to easily accommodate such network
changes. Fairness, latency, throughput and bandwidth utilization are
generally the primary concerns in traditional wireless voice and data
networks.
2.6.4 Security in Wireless Sensor networksWSN is an emerging technology that are used in applications, including
wildlife and ocean monitoring, manufacturing machinery performance
monitoring, building safety and earthquake monitoring, and many military
applications. Because of the nature usage of the WSN, traditional security
techniques used in traditional networks cannot be applied directly. Sensor
nodes are often deployed in accessible areas, presenting the added risk of
27
physical attack. Besides, sensor networks interact closely with their physical
environments and with people, posing new security problems. Therefore,
existing security mechanisms are inadequate [32].
2.7 Routing protocols in Sensor networksIn the section, we make introduce different routing protocol for WSN.
Besides, a detailed explanation of the AODV would be presented as it
integrated with the proposed energy based scheduling schema.
2.7.1 Ad Hoc On-Demand Distance Vector Routing Protocol
(AODV)AODV routing protocol is another on demand routing protocol. Routes
are established when they are required. Compared with DSR, AODV
maintains the routing table in each node rather than in each data packet
header.
2.7.1.1 Route DiscoveryWhen the source node initiates a route discovery process to the
destination, a RREQ packet will be broadcast to the network. When its
neighbours receive this packet, they will check the source address and
request id, which can uniquely identify this packet. If it is the first time they
receive this packet and they do not have the routing information to the
destination, they will rebroadcast it and the hop count of RREQ will be
increased by one. Otherwise, they will discard it. In addition, they will set
up a backward entry those points to the source in their routing table.
Eventually, the destination or any intermediate node that has routing
information to the destination receives this RREQs packet. Then a RREP
packet will be sent back to the source [48].
Figure 2.3 illustrates the process of route discovery. The RREP packet
will travel back to the source in the reverse direction. In addition, all
intermediate nodes will set up a forward entry in their routing table to the
28
destination. When the RREPs packet arrives at the source, the route
discovery process is completed.
Figure 2.3 AODV route discovery
The RREP packet will travel back to the source in the reverse direction.
In addition, all intermediate nodes will set up a forward entry in their
routing table to the destination. When the RREPs packet arrives at the
source, the route discovery process is completed. When the route is set up
successfully, the source can start sending data packets to the destination.
Each routing entry has an expiration period. If this routing entry is idle for a
while, this route will be considered broken and a RERR packet will be
generated and sent back to the source indicating that the destination is
unreachable.
Each node can get to know its one-hop neighborhood by using HELLO
packets. The purpose of HELLO packets is to inform its neighborhood that
is still alive. Hello packets will not be forwarded. When a node receives a
HELLO packet, it updates the corresponding lifetime of the neighbor
information in its routing table. This local connectivity management should
be distinguished from general topology management to optimize response
time to local changes in the network.
29
In addition, AODV uses sequence numbers to solve the loop problem.
Each node maintains its own sequence number. When it sends a RREQ, its
sequence number will be incremented. In addition, when it sends a RREP,
its own sequence number will be the maximum of the current sequence
number and the sequence number in the RREQ.
2.7.1.2 Route MaintenanceWhen a route which is active is down due to node failure, the
neighborhood nodes are notified through a RERR message. When a node
receives an RERR, it marks its route to the destination as invalid. When a
source node receives an RRER, it can reinitiate the route discovery.
2.7.1.3 Control MessagesThere are three kinds of control packets used in AODV. Control
messages used for the discovery and breakage of route are as follows [47]:
Route Request Message (RREQ)
A route request packet is flooded through the network when a route is
not available for the destination from source. This packet is used in a
route discovery operation when the destination is not available. It
includes the addresses of the source and the destination.
In addition, it has request ID, hop count and the sequence number of
the source and the destination. Figure 2.4 shows the fields contained
in a RREQ packet.
Source
Address
Request ID Source
Sequence
Number
Destination
Address
Destination
Sequence
Number
Hop
Count
Figure 2.4 AODV RREQ packet
30
After receiving of request message, each node checks the request ID and
source address pair. The new RREQ is discarded if there is already RREQ
packet with same pair of parameters. A node that has no route entry for the
destination, it rebroadcasts the RREQ with incremented hop count
parameter. A route reply (RREP) message is generated and sent back to
source if a node has route with sequence number greater than or equal to
that of RREQ.
Route Reply Message (RREP)
If the intermediate node knows the route to the destination or the
destination receives a RREQ packet, they will send a RREP packet
back to the source. Figure 2.5 shows the fields contained in a RREP
packet.
Source
Address
Destination
Address
Destination
Sequence
Number
Hop Count Life Time
Figure 2.5 AODV RREP packet
Route Error Message (RERR)
The neighborhood nodes are monitored. When a route that is active is
lost, the neighborhood nodes are notified by route error message
(RERR) on both sides of link.
Unreachable
destination IP
address
Unreachable
destination
sequence
number
Additional
unreachable
destination IP
Address
Additional unreachable
destination sequence
number
Figure 2.6 AODV RERR packet
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HELLO Messages.
The HELLO messages are broadcasted in order to know
neighborhood nodes. The neighborhood nodes are directly
communicated. In AODV, HELLO messages are broadcasted in order
to inform the neighbors about the activation of the link. These
messages are not broadcasted because of short time to live (TTL)
with a value equal to one.
Destination
IP address
destination
sequence
number
Originator IP
Address
Originator sequence
number
Figure 2.7 AODV Hello packets
2.7.2 Dynamic Source Routing (DSR)The Dynamic Source Routing (DSR) Protocol is a source-routing on-
demand protocol. The difference in DSR and other routing protocols is that
it uses source routing supplied by packet’s originator to determine packet’s
path through the network instead of independent hop-by-hop routing
decisions made by each node. The two major phases of the protocol are:
route discovery and route maintenance. It is a simple and efficient routing
protocol designed specifically for use in multi-hop wireless ad hoc networks
of mobile nodes [45].
When the source node wants to send a packet to a destination, it looks up
its route cache to determine if it already contains a route to the destination.
Each node maintains route caches containing the source routes that it is
aware of. The node updates entries in the route cache as and when it learns
about new routes. If the node finds that an unexpired route to the destination
exists, then it uses this route to send the packet. On the other hand, if the
node does not have such a route, then it initiates the route discovery process
by broadcasting a route request packet throughout the network [46].
The route request packet contains the address (usually the IP) of the
source and the destination, and a unique identification number. Each
32
intermediate node checks whether it knows of a route to the destination. If it
does not, it appends its address to the route record of the packet and
forwards the packet to its neighbors. To limit the number of route requests
propagated, a node processes the route request packet only if it has not
already seen the packet and its address is not present in the route record of
the packet [45, 46].
DSR uses Route Error packet to flag invalid links (links that are now
unreachable due to mobility). When a node faces a fatal transmission
problem at its data link layer (when the retransmit limit is reached), it
generates a Route Error packet. When a node receives a route error packet
informing it of a link that is now unusable, it removes the invalid link from
its route cache. All routes that contain invalid link are truncated to that
point.
In route discovery process, source node checks whether it has a route to
this destination in the route cache then it sends packets to a destination. If
the destination address is not in the table, the source node will initiate a
route request (RREQ) packet for broadcast. Nodes receiving this RREQ will
first see whether the destination is itself. If yes, it will reply with a route
reply (RREP) packet unicast to the source node with the reverse path the
RREQ traversed. Otherwise this node is an intermediate node. Intermediate
nodes who receive this packet should first check the freshness of this RREQ.
If the intermediate nodes have received this RREQ recently, it will ignore
the packet; or else the intermediate node will rebroadcast this RREQ,
another alternative is that the intermediate node replies the RREQ when it
knows a route to the destination.
Source node should be notified using route error (RERR) packets when
there is a break on any link on the route which is in use. Source node
receiving the RERR will delete all the routes which contain the reported
link. A new RREQ will be generated when the route is still needed.
The advantages of the DSR protocol include easily guaranteed loop-free
routing, support for use in networks containing unidirectional links, use of
only "soft state" in routing, and very rapid recovery when routes in the
33
network change. The DSR protocol is designed mainly for mobile ad hoc
networks of up to about two hundred nodes. It is designed to work well with
even very high rates of mobility [46].
2.8 SummaryIn this chapter, we made an overview on the Wireless sensor networks.
This overview took into account many topics regarding the WSN. These
topics include architecture, design objectives, challenges and research areas.
Then, we explain in details routing protocols which are related to our work.
In the next chapter, we will introduce scheduling techniques which are
used in WSN.
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Chapter 3
Scheduling Techniques in Wireless Sensor
NetworksScheduling is the primary mechanism available to intermediate nodes
achieve their deadlines. The goal of real-time scheduling algorithms is to
ensure that critical timeliness constraints, such as response time and deadlines,
are met. When necessary, decisions are made that favor the most critical timing
constraints, even at the cost of violating others [49].
This chapter is divided into four sections. The first section gives a breaf
overview on the scheduling in WSN. Then, the types of packet delays are
mentioned. After that, the types of the scheduling schemas used in WSN, are
introduced with a brief explanation for each one of them.
3.1 Scheduling in WSNIn the applications based on sensor networks, the scheduling algorithms
have to work in a distributed manner. The scheduler residing on each node
makes scheduling plans without any global knowledge [50].
Traditional real-time scheduling algorithms are designed for centralized
systems such as a mainframe. Figure 3.1 shows a simple model of the function
of a scheduler. For an input set of parameter values of a specified job, the
scheduler outputs the priority of this job that is used for arbitrating scheduling
on a critical resource.
SchedulerSchedulingParameters ofspecified job
Priority ofthe job
Figure 3.1 Scheduler function model
35
The challenge here is how to schedule multiple data packets at each node
independently so as to minimize the global data transmission miss ratio.
Besides minimizing the global transmission ratio, minimizing energy
consumption is another important challenge. Communication protocols for
sensor networks must have the ability to provide real-time assurances, data
transmission assurance and energy [26].
The nature of traffic in wireless sensor networks is bursty. It can cause the
exceed of the network resources. In addition, the ad hoc nature of multi-hop
sensor networks makes it difficult to schedule network traffic centrally as in
traditional real-time applications. The scheduler residing on each node makes
scheduling plans without any global knowledge. How to schedule multiple data
packets at each node independently so as to minimize the global data
transmission miss ratio is the challenge here [51, 52].
Existing real-time data communication work have developed packet
scheduling schemes. These schemes work on prioritizing packets according to
their deadlines. Packet prioritization cannot completely support real-time data
communication requirements nor the energy consumptions constrains.
Examples of the most used real-time sensor network protocols are the Basic
Priority Scheduling, RAP, Just in Time Scheduling (JiTS). In our thesis, we
will focus on the Basic Priority Scheduling in our simulations.
3.2 End-to-End Packet Delay in WSNEnd-to-end delay refers to the time taken for a packet to be transmitted from
source to destination across a network. For data communications across WSN,
the problem is providing timeliness guarantees for multi-hop transmission
under energy constraints. Any packet in the network, whether it is control or
data packets, needs to traverse multiple hops from the source to the sink
according to its deadline [53, 54].
36
3.2.1 End-to-End Packets Delay ComponentsThe transport delay and the queuing delay are the main components of the
end to end delay. They affect the packet end to end delay during transmission
from source to destination.
3.2.1.1 Transport DelayThe transport time of packets from the source to sink are affected by the
processing delay and the propagation delay. Minimizing the transport time of
each packet is not close enough to minimize the end to end delay. The queuing
delay at intermediate nodes is more important. As most of packets time, is
consumed at intermediate nodes. The transport delay happens because of two
delays:-
Processing Delay
While the transmission of control and data packets through intermediate
nodes, specific processing might be necessary. Specific processing might
be necessary, for some applications.
Transmission Delay (or store-and-forward delay)
The propagation delay of packets is determined by the bandwidth and
the size of the message. In a network based on packet switching such as
WSN, transmission delay is the amount of time required to push all of
the packet's bits into the wire. In other words, this is the delay which is
caused by the data-rate of the link.
3.2.1.2 Queuing delayIt is the time spent in the queues at each intermediate nodes on the path from
the source to the sink. In other words, the time a job waits in a queue until it
can be executed. It is a key component of network delay. As a packet is
received at an intermediate node, it is placed in the MAC layer incoming
queue. The queuing delay may be controllable by a scheduler, since a queue is
used to store a data packet temporarily at any forwarding node. When the
37
network layer receives from the queue, it looks at the packet and decides where
it needs to be forwarded next. The routing layer places the packet in a local
queue while making routing decision. Consequently, the packet is placed in the
MAC layer outgoing queue to be forwarded to the next hop. Since a queue is
used to store a data packet temporarily at any forwarding node, the queuing
delay may be controllable by a scheduler.
The queuing delay may grow to be the main part of the end-to-end packet
transport time especially under high load. More specifically, under moderate to
high data generation rates, congestion and other reasons, the queuing
contribution to delay can far outgrow the physical transmission and processing
contributions.
3.3 Main Scheduling Concepts in Wireless Sensor
NetworksIn WSN, there are different ways in packet scheduling. Scheduling could be
done according to deadline, where packet deadline is the main constraint that
affects the packet sending decision. Other technique depends on the available
time that a packet may have through its journey to the destination [50]. Figure
4.2 shows the types of packet scheduling.
3.3.1 Deadline-based SchedulingIn a wireless sensor network, the scheduling decision is made at each node
independently. The deadline-based scheduling procedure schedules all
incoming data packets based on their deadlines. If a data packet has an earlier
deadline, it receives a higher priority than another with later deadline. These
scheduling algorithms do not differentiate the up-to-date real-time status of
each packet through its forwarding path and therefore may hurt the overall
performance of the real-time scheduling system.
38
3.3.1.1 Rate Monotonic SchedulingRate monotonic scheduling is a kind of fixed-priority scheduling strategy, it
is a deadline-based scheduling algorithm. The scheduling decision has to be
made distributedly. Once the priority of one task is identified according to its
periodicity, it will not change with time. A task in smaller periodicity has
higher priority. RM can schedule a group of tasks while other fixed priority
strategies can. Fixed-priority strategy is more suitable for wireless sensor
network operating system, because it needs to be scheduled one time before
running. Fixed-priority will be able to ensure the cyclical behavior, and the
tasks are scheduled only in one queue. RM's shortcoming is the lack of
flexibility due to its unchanged in running time. Therefore, it is not suitable for
working during running [51].
RMS is the optimal static-priority algorithm. If a set of tasks cannot be
scheduled using the RMS algorithm, it cannot be scheduled using any static-
priority algorithm. A major limitation of fixed-priority scheduling is that it is
not always possible to fully utilize the CPU [55]. Even though RMS is the
optimal fixed-priority scheme, it has a worst-case schedule bound of:
PacketScheduling
DeadlineBased
RateMonotonicScheduling
EarliestDeadline first
Real-Time
Lagging FlowFirst
AlgorithmBasic Priority
VelocityMonotonicScheduling
Just in TimeScheduling RAP
Figure. 3.2. Classfications of Packet scheduling techniques
39
= ∗ (2 − 1) (3.1)
Where:-
n is the number of tasks in a system.
is the worst-case schedule bound
The worst-case schedulable bound for one task is 100%. However, as the
number of tasks increases, the schedulable bound decreases, eventually
approaching its limit of about 69.3% (ln2, to be precise). It is theoretically
possible for a set of tasks to require just 70% CPU utilization in sum and still
not meet all their deadlines.
3.3.1.2 Earliest deadline firstEarliest deadline first (EDF) or least time to go is a scheduling algorithm
used in packet scheduling. It places packets in a priority queue. Each packet is
assigned a sending priority according to its deadline. The closer the deadline of
a packet, the higher is its sending probability.
3.3.2 Real-Time Architecture for Sensor NetworksThe key role of a scheduling algorithm in real-time communication
architecture is to schedule the incoming packets for forwarding. Traditional
first come first served scheduling may not work well in real-time applications.
As, packets have different remaining times to their deadlines, besides the
difference in the distances to reach their destination. Most of the scheduling
schemas take neither the energy consumption nor the wireless sensor network
lifetime in the calculations of the priorities. In the following sections, we
present some scheduling schemas.
40
3.3.2.1 Basic Priority SchedulingIt is a technique for scheduling, which is the default scheduling schema in
the NS-2. It depends on prioritizing the packets according to their usage.
Priority values are assigned to every packet in the network regardless its energy
consumption. High priority values are usually given to control packets, while
medium or low priority values are given to data packets. Data Packets of same
type are served in FIFO order [56].
3.3.2.2 Lagging Flow First AlgorithmLagging Flow First (LFF) is a location-free algorithm proposed in [57]. This
technique considers not only how to deliver the packets to arrive at their
destinations within their deadlines but also how to minimize the maximum
degradation. The degradation value is defined as ϵ:
ϵ = 1 − − (3.2)
Where:-
is the number of packets that flow i actually successfully
delivered
is the number of packets that flow i was supposed to deliver
is acceptable packet loss rate.
This technique maintains two queues, one is a reservation list to hold the
packets that will be delivered, and the other is a buffer to hold packets that do
not have spots in the reservation list. This technique is composed of two
phases. In first phase, whenever a packet is available to be scheduled, a time
slot could be reserved based on its deadline. Then this packet could be inserted
into a reservation list if it is possible. Otherwise, this packet will be inserted
into the second queue. In the second phase, a packet is scheduled in the
41
reservation list. Therefore, we can observe that the packets in the reservation
list have higher priorities. This algorithm takes into consideration both the
deadline and the degradation of the traffic flow.
3.3.2.3 Velocity Monotonic Scheduling AlgorithmVelocity Monotonic Scheduling Algorithm is a location-based algorithm
proposed by [57]. The basic idea of this algorithm is to prioritize packets based
on their velocities. The definition of packet's velocity is the ratio of the distance
that it needs to travel to the time before its deadline. There are two versions of
velocity monotonic scheduling: static VMS (SVM) and dynamic VMS (DVM).
VMS improves the number of packets that meet their deadlines because it
assigns the “right” priorities to packets based on their different urgencies on the
current hop. VMS also solves the fairness problem in sensor networks because
packets that are far away from the base station will tend to have higher
priorities when it competes against other packets that are closer to the
destination.
VMS calculates the required packet “velocity”, which is used as its priority,
from the deadline and distance between source and sink. In Static VMS, the
velocity is computed once at the source. In Dynamic VMS velocity is
recomputed at intermediate nodes. It also modifies the MAC layer back-off
scheme to schedule packets according to priority. In the following section, we
explain in details the static and dynamic versions of VMS [58].
A. Static Velocity Monotonic SchedulingIn Static VMS (SVM), packets are prioritized based on a fixed requested
velocity. Velocity is computed at packet generation time. The values of
parameters used by prioritizing at any intermediate node are that of the data
source, not the forwarding node. All intermediate nodes have a separate queue
for each priority level and packets of higher priority are always forwarded
42
before packets of lower priority. Since the priority is fixed at the beginning, an
intermediate node cannot change it even if any unpredictable delay occurs. So
the velocity is fixed or static and defined as follows:
= (3.3)
For routing protocols with different policies, the distance between source
and destination is measured in different ways. The distance is measured in
number of hops, when using shortest path routing. For geometric routing, it
would be measured in Euclidean distance. The shortcoming of SVM is that
since the delay times of packets at intermediate nodes are unpredictable, it is
unable to increase the priority of a packet that is unexpectedly delayed, or
reduce the velocity of a packet that is lucky enough to make quick progress
initially towards the destination.
B. Dynamic Velocity Monotonic Scheduling (DVM)Dynamic VMS recalculates the velocity and resulting priority at each
intermediate node. The value of velocity is decided by function:
= (3.4)
The advantage of dynamic VMS is that an intermediate node has an ability to
adjust the priority based on the specific situation. Table 3.1 shows how DVM
and SVM are calculated for a packet between node a and node b.
43
Table 3.1: Packet priorities when different VMS policies are used
VMS policy At node a At node b
Static VMS distance(a, sink)E2E Deadline distance(a, sink)E2E DeadlineDynamic VMS distance(a, sink)E2E Deadline distance(b, sink)E2E Deadline − Elapsed Time
3.3.2.4 Just in Time Scheduling (JiTS)The Just in time scheduling is a scheduling scheme that is used for real-time
data communication in sensor networks [59]. This approach overcomes the
shortcoming of other real-time approaches by setting target transmission times
for the packets according to their deadline and the remaining distance along the
path to achieve more effective communication by allocating the slack time
(time until the deadline) among the intermediate hops. JiTS delays data packet
transmission during forwarding for a duration that correlates with their
remaining deadline and distance to the destination. Intuitively, this helps in
heavy-traffic communication environment by making sure that priority
inversion does not occur due to a node with low priority packets sending. Also,
it helps in preventing a node with high priority packets from doing so. The
Estimation of Transmission Delay (ETD) is used to approximate the MAC
layer transmission delay. Since this time is spent below the network layer, the
scheduling cannot directly affect it.
Before a data packet reaches the sink, the end-to-end transmission and
processing delay cannot be obtained. Therefore, previous measurements of
delay were used to estimate the overall delay: it is called this estimate the end-
44
to-end Estimate of Transmission Delay (EETD). Summing the ETD’s of a data
packet hop by hop during its forwarding can lead to inaccurate estimates since
one hop ETD can fluctuate significantly. Therefore, we use the following
function to decide the EETD:
EETD = ETD . (3.5)
Where:-
The distance can be measured in different ways.
Different JiTS scheduling policies can be developed based on the allocation
of the available slack time among the different hops. The target transmission
times are either set by the source or computed at intermediate hops based on a
known algorithm. In the base JiTS algorithm, the target transmission time is set
to be equal at all hops and is determined as follows:
Target Delay = ( , ) . (3.6)
Where:-
α is a constant safety factor for insurance that the real-time
deadline would be met.
Packet priority is determined by the Target Delay. The time a packet is
delayed in the queue can be used as the key to a priority queue that holds the
packets to be transmitted. The end-to-end transmission and processing delay is
considered along with the queuing delay, by considering the end-to-end
deadline, distance and EETD.
45
A. Static Just-in-Time SchedulingIn static JiTS, the target delay is set with the values of parameters at the data
source. In equation 3.6, the end-to-end deadline is fixed at the data source; the
EETD is measured with the ETD of forwarding node and the distance from
source to sink (X is the data source). So even we call it static, the different
ETD’s of forwarding nodes would make the target delay at each node different.
B. Dynamic Just-in-Time SchedulingIn dynamic JiTS, the target delay is re-set at each forwarding node with the
local value of parameters. In Equation 3.4, the end-to-end deadline of a packet
at some forwarding node is the remaining slack time, measured by E2E
Deadline − Elapsed Time. The EETD is decided by the one-hop ETD of the
forwarding node and the distance from it to the sink. It is not the distance from
source to sink. So, the dynamic JiTS is able to continuously refine the priority
of the packet.
C. Non-linear Just-in-Time SchedulingIt is possible to allocate the available slack time non-uniformly among the
intermediate hops along the path to the sink. For example, it is desired to
provide the packets with extra time as it gets closer to the sink. The anticipation
is that in a gathering application, the contention is higher as the packet moves
much closer to the sink. Different policies can be developed to break down the
available time. We explore the following policy:
Target Delay = . (3.7)
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3.3.2.5 RAP: a Real-time Architecture for Sensor NetworksRAP is a real-time framework developed at the University of Virginia [58].
RAP uses Velocity Monotonic Scheduling (VMS) to prioritize the data packets.
RAP does not consider the queuing delays of data packets; once the packet is
assigned a priority it remains at that priority regardless of queuing delay. RAP
also modifies the MAC layer back-off schemes to schedule packet
transmission. The main design goal of RAP is to develop a fair scheduling
algorithm for data dissemination in a distributed wireless sensor network, so as
to minimize the miss ratio of real-time data traffic. RAP requires support from
several layers in the network, which represents a significant deployment
barrier, especially for heterogeneous networks. In RAP, each incoming data
packet is assigned a priority by VMS scheduler based on its requested velocity,
and then queued into the priority queues before it is forwarded.
3.4 SummaryIn this chapter, we make a brief introduction of scheduling schemas in
WSN. This introduction includes the definitions of the scheduling process in
WSN. Then, we explored the types of end to end delays in WSN. Finally, we
introduced the some scheduling schema and algorithms used in WSN,
classified according to their packet priority assignment process.
In the next chapter, we will introduce in details our proposed energy based
scheduling schema.
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Chapter 4
Proposed Energy Based Scheduling Scheme
The key role of a scheduling algorithm in real-time communication
architecture is to schedule the incoming packets for forwarding. Traditional
FCFS scheduling does not work well in real-time applications because packets
have different remaining times to their deadlines, but also different distances to
reach their destination. In the context of sensor networks, packet scheduling
should be both deadline-aware and distance aware. Deadline-aware means that
a packet’s priority should relate to its deadline, the shorter the deadline, the
higher the packet priority. Distance aware means that a packet’s priority should
relate to its distance from the destination, the longer the distance, the higher the
packet priority.
The primary challenges here are how to prioritize and schedule packets.
Other challenge in real-time sensor network applications is how to carry out
sensor data dissemination given source-to-sink end-to-end deadlines when the
communication resources are scarce. In a sensor node, energy is consumed by
sensing, communication and data processing. More energy is required for data
communication than for sensing and data processing.
In this chapter, a new scheduling scheme that will not only prioritize packets
according to their deadlines but also according to their sizes, energy
consumption during transmission and energy path level. The new scheme
efficiently manages packet dropping at each node in order to avoid dropping
packets, which consumed high energy during transmission. Moreover, it does
not require any support from or changes to the lower layer protocols. In
addition, the new scheme can work with Ad hoc On Demand Distance Vector
(AODV) Routing Protocol.
48
4.1 Main Idea of the Proposed SchemeEnergy usage in packet transmission is much greater than its usage in data
processing and sensing. Efficient usage of sensor's energy resources and
maximizing the network lifetime are the main design considerations for the
most proposed protocols and algorithms. However, depending on the type of
application, the generated data packets may differ in their energy
consumptions. This section, will introduce a new scheduling scheme called
Energy Based Scheduling Scheme
A. Energy Based Scheduling SchemeThe primary challenges of packet prioritizing according to deadline or
available time slack, is that it may lead to dropping high energy valuable
packets. Packets arriving from far sources may consume much energy.
Dropping these valuable energy packets may lead to shorten the network
lifetime. In addition, packet transmission path is a major issue that should be
considered in packet scheduling. Packet transmission decision should not only
be affected by the packet deadline, but also by packet energy consumption and
packet transmission path. Routing protocols are responsible for the path
selection. According to the selected path, packets are sent from source to
destination. During packet transmission, each node queues the packets to its
buffer. . Energy Based Scheduling Scheme schedules the buffered packets at
each node, according to specific parameters. This Scheme is the primary
contribution of this thesis.
4.2 Scheme ParametersThe proposed scheme depends on the fact, that energy usage in packet
transmission is so greater than its usage in data processing and sensing.
Scheduling schemes have the responsibility of whether to drop, delay or send
the packet according to some measures, form node queues. The problem is how
49
to prioritize packets according to four constraints packet deadline, packet size,
packet energy consumption during transmission and packet energy path level.
According to this measure, we can find the path stability and strength that a
packet uses through its transmission from source to sink. The following
information is needed to schedule packets in the proposed scheme.
4.2.1 Packet DeadlineThis information is provided by the application in the data packet. It is
required by any real-time data communication application. According to this
information, each node might drop or delay the packet for a particular time.
When any packet reaches its deadline, the corresponding node, which is
holding that packet in its queue, must drop it.
4.2.2 Packet SizeIn WSN, there are two types of packets. They are control packets and data
packets. Control packets are used by the routing protocol for handling data
delivery. Data packets are the packets that are responsible for carrying the
required sensed data from a particular node to the destination. Control and data
packets contain reserved bits that will be used by our scheme. In the proposed
scheme, packet size might be used in prioritizing packets.
4.2.3 Packet Energy Path LevelIt is a new measure that is required by the proposed scheme. This energy
measure reflects the value of the energy nodes across a specific path.
According to this measure, we can find the path stability and strength that a
packet uses through its transmission from source to sink. This measure is
calculated at each node which a packet uses during transmission.
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4.2.4 Packet Energy Consumption during TransmissionDuring packet journey from source to destination, each node receives the
packet, buffers it and retransmits it to the destination or the next node close to
the destination. In the proposed scheme, Packet Energy Consumption during
Transmission is an important factor in prioritizing packets, as energy
consumption in packet transmission is so greater than its usage in data
processing and sensing.
4.3 Scheme EquationsBuffered packets at each are assigned sending priorities in a priority queue.
The priority queue holds the packets to be transmitted. In the proposed scheme,
each assigned priority is according to packet deadline, packet size, and packet
energy path level and packet energy consumption during transmission. These
four parameters have major effect on the network energy measures. These
measures might be the network life time or the energy consumption for the
goodput. Some other network measures might be affected when appling the
scheme. Through the next chapters, these measures are used in comparing the
proposed scheme against.
The following notations are used in the discussion.
PD: packet deadline
PS: packet size
PEP: packet energy path level
PEC: packet energy consumption during transmission
Subscript ‘i’ is often used with these parameters to indicate that they are for
a node i, while subscript ‘x’ is used to indicate that they are for a packet x.
For packet x, PEPx at node d, is calculated through the following equation:
51
( ) = ∑ ( )∈ (4.1)
where:-
PEPx(d) is packet energy path level at node d for packet x
E(i) is the current energy for node i while receiving packet x
IEi is the initial energy for node i.
R denotes the set of nodes that packet x uses through
transmission from its source to node d. It shows the path strength
and stability according to the energy of each node.
To calculate the PECx for packet x at node d, we use the following equation:
( ) = ∑ ( )+ ∑ ( )∈∈ (4.2)
where:-
PECx(d) is the packet energy consumption during
transmission of packet x at node d
ETx is the energy transmission cost for packet x
ERx is the energy cost for packet x reception.
RTx and RRx are set of nodes used for transmission and
reception respectively.
So, the problem is simplified to find a suitable priority for each packet
during its transmission. This priority should consider packet deadline, packet
size, and packet energy path level and packet energy consumption during
transmission. According to this priority, any packet buffered in a queue, could
be sent or delayed. Therefore, the equation used for packet priority calculation
in our scheme should reflect the effect of its related parameters. In order to
apply the proposed scheme, the maximum packet size and deadline values,
52
used by the network, are required. These values are used to normalize the
packet size and deadline.
The following equation is used to calculate the packet sending priorities
(PSP) for each packet x at each node d in:
( ) = × ( )( )× . (4.3)
Where:-
PSPx(d) is the packet sending priorities of packet x at node d
PECx(d) is the packet energy consumption during transmission of
packet x at node d
PEPx(d) is packet energy path level at node d for packet x
α is a constant factor for insurance that the packet deadline would
be met
Nx represents the number of nodes, which packet x used
PSN and PDN are the normalized values for packet size and
deadline.
According to PSP value, each node would decide whether to send the packet
at once or delay it. This scheme would help in increasing the network lifetime
for the remote node of the networks. Packets from remote nodes would have
increasing sending priorities through their path to the destination. We use PEP
in order to overcome the problem of higher sending priorities for packets from
remote nodes.
During the packet trip from its source to destination, it is buffered in every
node queue across its path. Each node carries the responsibility of calculating
the PSP for each packet in its buffer. In order to get the value of PSP for each
packet, we modify the packet header by adding new header parameters to it.
These parameters will be the values of PEP, PEC and the number of visited
53
nodes without the current node. Using these parameters, each node will be able
to calculate PSP for each packet in its queue. Before packet transmission, the
node transmitting the packet must update the new added parameters in the
packet header.
4.4 Priority QueueManaging limited resources such as bandwidth on a transmission line can be
done through Priority queuing. The output of energy based scheduling scheme
is the queuing of packets, which is assigned sending priorities. This queue is
used by the routing protocol to decide which packet to retransmit according to
the assigned priority (by passing it to the MAC layer). A single priority queue
for packet forwarding based on the computed target transmission time is used
by the energy based scheduling scheme. When the queue is full, the scheme
selects the packet at the head of the queue to immediately forward it instead of
dropping any packet in the queue.
If there was no heavy traffic through the current node and priority queue is
not almost full, the energy based scheduling scheme is not needed. The
proposed scheme can be disabled and packets are forwarded normally.
A single priority queue is used in the routing layer for forwarding packets. It
can better track the priority of data packets than the approach of several FIFO
queues with different priority levels.
4.5 Integration with routing protocolsIn this section, we will show how to integrate the proposed scheme with the
Ad hoc On Demand Distance Vector routing algorithm. AODV don’t have any
effect on the sending priorities, as they are assigned by the proposed scheme.
54
4.5.1 Energy Based Scheduling Scheme for AODVThe Ad hoc On Demand Distance Vector (AODV) routing algorithm is a
routing protocol designed for wireless mobile networks. It is selected as the
baseline routing protocol because it is an on-demand protocol without global
periodic routing advertisement. Besides, it consumes less overall network
bandwidth as the network is silent until a connection is needed. It creates no
extra traffic for communication along existing links [47]. AODV achieves
comparable results when it is used in wireless sensor networks and compared
with the common WSN routing protocols [60,61]. In [62 - 64] several updates
are applied to the AODV in order to make it applicable to be used in WSN.
4.5.1.1 Ad hoc On Demand Distance Vector (AODV) Routing
Protocol
The AODV was mentioned in chapter 2. Being a reactive routing algorithm,
AODV only maintains the routing paths which are used in packet transit. It is
considered a destination based reactive protocol, which avoids routing loops by
using of sequence numbers. In this protocol, the nodes use the sequence
numbers to avoid loops and take the path information as updated as possible.
When a source node wants to transmit information to a destination node, a
short route request (RREQ) message will be initiated and broadcast by the
source, with an estimated and pre-defined lifetime (TTL). RREQ is rebroadcast
until the TTL reaches zero or a valid route is detected. Each node, receiving the
RREQ will add a valid route entry in its routing table to reach the RREQ
source, called reverse route formation. When the RREQ reaches the destination
or a node that has a valid route to the destination, a route reply (RREP)
message is uni-cast by this node to the source. The RREP message will go to
the source, following the reverse route formed by the RREQ [47].
55
4.5.1.2 Scheme Implementation for AODVIn order to apply our scheme on AODV, the energy for each node in
transmission path and the energy consumption during transmission should be
assigned to packet, which used that path. For AODV, there are four types of
packets, which are used for routing and path discovery. They are Route
Request (RREQ), Route Reply (RREP), Route Error (RERR) and Route Reply
Acknowledgment (RREP-ACK). According to [11], each packet has a number
of unused bits, called reserved bits. The number of unused bits in each packet
is shown in Table 4.1. Our proposed scheme works on making use of these
unused bits to store the PEP and PEC for each packet, in order to use them in
calculations. Figure 4.1 shows how the proposed scheduling scheme reacts
with the different components of the WSN.
4.6 WSN Application adaptation
As we mention in section 2.3, WSN applications differs in its requirements
from one application to another. These differences are according to application
nature or usage. Some WSN applications, which are used in Battlefield
Monitoring in military applications, might need to have a better network life
time. In addition, deploying sensors in a battlefield to monitor the presence of
forces and vehicles, and track their movements, enabling close surveillance of
opposing forces, would make replacing low battery nodes, so hard and
Table 4.1: amount of reserved bits (unused bits)
AODV packet type Number of unused bits
RREQ 11
RREP 9
RERR 15
RREP-ACK 8
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dangerous. So, the calculated packet sending priorities (PSP) could be
compared to a threshold. According to this threshold, each node can take the
decision of whether buffering the packet for a period of time or immediately
forward it, regarding the energy packet consumption.
Figure 4.1 Scheduling Scheme in WSN architecture
According to Figure 4.2, we could find that low threshold packets with low
energy consumption have the same chance as packets with high energy
consumption and high threshold. However, high threshold value would give
packets with high energy consumption much better chance in retransmission
than other packets. The proposed scheme by default could assign sending
probability to packets depending on the consumed energy for each packet.
Sometimes, WSN application might require high threshold value in order allow
Data
Routing Agent
MAC Layer
Application Differentiator
Scheduling Scheme
DeadlineEnergy PathLevelData
Data SendingPriority Data
57
packets of high energy consumption to have much better sending probability.
The use of the threshold value and its effect on network lifetime and packet
delivery ratio would be disused in the next chapter.
4.7 Properties of proposed Energy Based Scheduling Scheme
The proposed scheme has some important features and properties that
differs it from other scheduling algorithms. These features and properties give
our scheme advantages in the energy and lifetime fields. In this section, we will
show the features of our scheme.
4.7.1 Routing protocol independentThe main advantage of the Energy Based scheduling scheme is the routing
protocol independency. The scheme can work with any routing protocol. The
required parameters for the scheduling scheme can be calculated easily at any
node, without any support from the routing protocol or the MAC layer.
However, a trade off might appear if the used routing protocol does not have
Figure 4.2: Packet Energy consumption vs. the threshold
Sending Priority
Threshold
Pack
et E
nerg
y co
nsum
ptio
n
58
reserved bits in the used packets. Moreover, additional bits to any packet
format might lead to an increase in the networks energy.
4.7.2 MAC layer protocol independentUnlike the JiTS, the Energy based scheduling scheme does not require
MAC layer support for prioritized scheduling. This makes Energy based
scheduling scheme readily deployable on existing infrastructure. The Energy
based scheduling does not require MAC layer support for prioritized
scheduling or for tracking delay.
4.7.3 Energy awareThe important feature of the proposed scheme is its energy awareness. Any
priority assigned or packet dropped or retransmitted, is done according to some
energy measures. This way in taking decisions helps in increasing the network
life time and decreasing the energy consumption for the goodput.
4.7.4 QoS awareMinimizing the packet loss ratio is an important factor in the proposed
scheme. Moreover, decreasing the packet loss should be achieved with an
increase in the network lifetime and the energy consumption for the goodput.
4.8 Overall Proposed SchemeIn this section, we will show in steps how the proposed energy based
scheme works when a packet is queued in the queue of a node in WSN. When
a packet is buffered in the nodes the following should be done by the proposed
scheme:-
If the packet is buffered in its source node
1. The current node energy is normalized according to the node
initial energy and stored in the node header.
59
2. The amount energy consumed by node for send a packet is
normalized according to current nodes energy and stored in the
packet header.
If the packet is buffered in an intermediate node
1. The current node extracts the values of the previous node(s)
energy and the amount of energy consumed by the node during it
journey.
2. The node adds the value of the current node energy after
normalization to the extracted energy value.
3. The PEP is calculated for this packet according to equation (4.1)
4. The node adds the value of the amount energy consumption after
normalization to other extracted energy values
5. The PEC is calculated for this packet according to equation (4.2).
6. The PSP is calculated according to equation (4.3)
7. According to the value of PSP, the decision of whether to send or
delay a packet in the queue is taken.
4.9 SummaryIn this chapter, we have presented the proposed energy based scheduling
scheme and its integration with the AODV.
The chapter starts with brief introduction of the effect of the energy on
WSN which followed by introducing the proposed scheduling energy based
scheme. Then, we present equations used in our scheme in order to calculate
the packet sending probability for every packet.
Next, we show how to integrate the proposed energy based scheme with
AODV routing protocol. Then, we present the steps used in calculating packet
send probability.
The next chapter will show how our scheduling scheme integrated with
AODV, works in WSN. Also, we will compare it with other routing protocols
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Chapter 5
Simulation of the Scheme and Results
The primary goal of the research is to develop a scheduling scheme, which
fulfills the demands for minimizing the energy consumption and maximizing
the WSN life time. A great attention should be paid for the QoS and fairness
while achieving these demands. The previous chapter presented the proposed
energy based scheduling scheme in wireless sensor networks. It shows the
mathematical equations, which are used in the proposed scheme in assigning
send priorities to data and control packets. In this chapter, a comparison is done
between the proposed scheme and the Basic priority scheme.
Simulation is the most deployed method to evaluate algorithms and
protocols for WSNs. It enables the researcher to deal with complex topologies,
network scalability, and repeating of experiments. Simulations are also carried
out at low cost, for these reasons simulation gains a lot of popularity as
evaluation method. In the simulation, NS2 was used as the network simulator.
The proposed scheme would be compared according to some network metrics.
This chapter introduces the evaluation and comparison of the proposed
energy scheme against the Basic priority scheme using simulations. The
comparison is done against the normal AODV, DSR and DSDV.
5.1 The Network Simulator (NS-2)The Network Simulator (NS-2) was used as simulation software to
accomplish the performance evaluation in this thesis. NS-2 is a discrete-event
simulator, which can be obtained as public domain software. Currently, it is
widely used in all kinds of network research areas such as, LAN, Internet and
wireless sensor network. It is free and open source software that makes NS very
popular and is used in several research projects [67].
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NS-2 is an object oriented simulator developed as part of the VINT project
at the University of California in Berkeley. The project is funded by DARPA in
collaboration with XEROX Palo Alto Research Center (PARC) and Lawrence
Berkeley National Laboratory (LBNL). Ns-2 is extensively used by the
networking research community. It provides substantial support for simulation
of TCP, routing, multicast protocols over wired and wireless (local and
satellite) networks, etc.
5.1.1 Why Network Simulator (NS-2)?Several extensions for NS-2 can be obtained from researchers worldwide. It
provides many useful tools such as NAM, trace file and TCL. In addition, many
protocols have already been implemented in this simulator for example, TCP,
UDP, many routing algorithms, multicast protocols and IEEE 802.1 1 DCF.
Therefore, it can concentrate on implementing and studying our scheduling
scheme.
NS-2 is written in both C++ and OTcl programming languages. The Code in
C++ is used for data path and in OTcl for control path. OTcl is an object
oriented language, which is an extension to the scripting language Tcl. OTcl is
an easy to use language that can be used to have rapid application development.
The OTcl linkage matches an OTcl object for one of the C++ objects to enable
the control of C++ objects to C++. NS-2 has also C++ objects, which operate
without the need of OTcl control. The simulator has modules that are
completely implemented in OTcl and are not in C++. NS-2 is controlled by
utilizing of user simulation scripts, which are written in OTcl [68].
The OTcl script maintains the main characteristics of the case study to be
simulated. An OTcl interpreter is used to set up the simulation configurations
and controls of C++ data path. NS-2 was firstly focused on wired networks and
later was extended to wireless and mobile hosts. Also, users can use NAM
which is a Tcl/TK based animation tool to observe network simulation. It
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provides network topology layout, packet transmission animation, and various
data inspection tools [68].
The simulation process of a protocol is achieved through the simulation
scripts in OTcl. Otherwise, the user needs to implement the protocol firstly in
C++. User can then simulate the protocol using simulation scripts written in
OTcl. The OTcl script maintains the main characteristics of the case study to be
simulated. An OTcl interpreter is used to set up the simulation configuration
and controls of C++ data path. As mentioned before, NS-2 was firstly focused
on wired networks and later was extended to wireless and mobile hosts.
5.1.2 Node Architecture in Network Simulator-2In NS-2, network physical activities are translated to events. Events are
queued and processed in the order of their scheduled occurrences. And the
simulation time progresses with the events processed. And also the simulation
“time” may not be the real lifetime as we “inputted”. It can configure transport
layer protocols, routing protocols, interface queues, and also link layer
mechanisms. We can easily see that this software tool in fact could provide us a
whole view of the network construction, meanwhile, it also maintain the
flexibility for us to decide. Thus, just this one software can help in simulating
nearly all parts of the network. This definitely will save us great amount of cost
invested on network constructing.
This thesis focuses on the implementation of IFq module and prioritized
MAC module. In this section, we mainly discuss the implementation of IFq
module. It is known that IFq module provides a buffer and a scheduling
algorithm. Therefore, one of our main tasks is to implement our proposed
algorithms to replace the original IFq algorithm. The architecture of the NS-2
MAC layer has been changed as shown in Figure 5.1. In this chart, the energy
based scheduling scheme is between the LL module and the MAC module. It
accepts packets from the LL module and selects a packet in terms of its
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scheduling algorithm. Then it transmits packets to the MAC module. The real-
time scheduling module contains the implementation.
Figure 5.1: architecture of the WSN node in NS-2
5.1.3 Simulation Process StepsIn order to evaluate, compare and study the effect and behavior of our
scheme, simulation is done against the Basic priority Scheme. Each time a
simulation is run the following steps are done.
1. Traffic pattern is generated by Matlab. These patterns connectivity of
sources in the OTcl script.
2. The user programs senario to be simulated with OTcl. This includes
event scheduler initiation, set up of network topology, starting and
ending of packet transmitting, setting values of corresponding data,
event log and visualization set up.
3. The Network Simulator executes the OTcl script.
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4. After executing of the OTcl script, the results are taken in form of trace
files. Each line in a trace file contains a packet event. It is very helpful
that tracing in NS-2 can be done at MAC level and at routing level. The
network simulator supports two trace formats that are called old and new
trace format. The new trace format is designed for the wireless traces.
The generated trace files are then analyzed by utilizing of scripts written
in a scripting language as AWK. NS-2 includes the NAM tool, which
enables the visualization of packets exchange.
5.1.4 The Simulation ScriptsSimulation scripts are the input to the network simulator, which include all
the information related to the simulation case study. The script begins usually
with the configuration of the simulation components of the network such as the
topography, the queues, the MAC protocol, the routing protocol and the
wireless channel.
The instructions to create the trace files are included in the simulation script.
The configuration of the mobile nodes is done and that is followed by the
creation of the nodes. The next part in the simulation script is to define the
initial positions of the nodes followed by definition of the mobility pattern of
the node.
5.2 The Hardware used in the SimulationAll simulation and programming works in this thesis were performed in
Window Server 2003 Enterprise Edition service pack 2 using the compiler gcc
2.9.6. All experiments were running on Dell PowerEdge 2800 tower server
with Intel Xeon CPU 3.40 GHz and 4 GB of RAM.
The simulation of wireless communication using NS-2 is a very time
consuming process. The execution of one simulation may take more than 10
hours. This simulation duration is increased by the increasing the traffic and
network simulation time. The NS-2 output trace files which requires a big
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memory space for storage. Some of the trace files have sizes of several giga
bytes. Appendix B will show the format of the trace files and the code required
for analyzing and processing the large size trace files.
5.3 Simulations Parameters and environmentIn our simulation, some parameters will be constant across all the
simulation, in order to have a clear view of the effect of the proposed scheme.
These parameters are shown in table 5.1. 100 sensor nodes are randomly
deployed in a square area in different scenarios to simulate our scheme [69].
The source and destination of traffic flows (CBR) are randomly selected as
well. All traffics are periodic of CBR type, with a constant packet size of 32
Byte. The physical and MAC layer parameters were set as in table 5.1 [69].
Table 5.1: Simulation Parameters
Mac layer Protocol IEEE 802.11
Transmission Radio Range 250 Meter
Data Packet Size 32 Byte
Data Rate 2 packet/sec
Simulation Area 1000 Meter X 1000 Meter
Number of Sensor nodes 100
Node Initial Energy 100 Joule
Transmission Power 0.024 Joule
Reception Power 0.0135 Joule
Figure 5.2 shows the network structure used in our simulations. The sink
node is placed roughly at the center of the network. Nodes publish data at the
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rate of 2 packets per second in order to simulate a fairly high load traffic
scenario. In this thesis, the proposed scheme is compared with the basic priority
scheduling. All nodes in the WSN have a queue size of 50. Figure 5.2 shows
three random deployments of 100 sensor nodes in a 1000 × 1000 m2 areas.
Figure 5.2a The position of the sink node in the simulated WSN
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Figure 5.2b The position of the sink node in the simulated WSN
5.4 The Simulations MetricsThe metrics measured in simulations, in order to compare the proposed
scheme against the Basic priority scheme. They are average end to end delay,
drop ratio, fairness index, average network lifetime and average energy
consumption fair received packets.
5.4.1 Average End to End Delay
Average end to end delay is defined as the delay of the successfully
transmitted packet from the source to the destination. This metric includes
queuing delay, retransmissions delays at MAC layer, propagation delay and
packet transfers times. It is an important factor to judge the effectiveness of a
network protocol. Equation 5.1 is calculated as follows.
= ∑ ( ) (5.1)
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5.4.2 Drop Ratio
The Drop ratio metric is defined as the number of unsuccessful received
packets during a specific time. It is another metric of throughput effectiveness
of a protocol. Equation 5.2 is used to calculate the drop ratio.
= (5.2)
5.4.3 Fairness Index
The fairness index is a measure used in network engineering in order to
determine whether users or applications are receiving a fair share of system
resources. Equation (5.3) is used to calculate the fairness index [70].
= ∑∑ (5.3)
Where:-
n represents the total number of sending nodes
x represent the throughput of every node.
5.4.4 Average Network lifetime
Wireless senor network lifetime is one of the most important constraints for
the network. Most, of routing, scheduling and MAC protocols focus on the
constraint. It is measured as the amount of time network spends until most of
its nodes are down.
5.4.5 Average Energy consumption for received packets
Energy consumption is another important constraint WSN. It is defined as
the average energy consumed by the whole network in order to deliver control
and data packets to the destination.
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Average energy consumption for received packets = Total Energy consumption by whole networkNumber of sussefuly received packets(5.4)
5.5 Simulation ResultsIn order to find the efficiency of our scheme, we compare it with the Basic
Priority Scheduling. This comparison is done against the AODV, DSR and
DSDV. Comparisons will be according to the previous mentioned simulation
metrics. After that, we show the effect of applying the threshold value on the
proposed and scheme and compare it to the Basic Priority Scheduling Scheme.
In all simulation, the energy based scheduling scheme is integrated with the
AODV (EB-AODV), as mentioned in the previous chapter. The sections show
the comparison of the EB-AODV against the AODV, DSR and DSDV.
5.5.1 Proposed scheme against AODV
In the following section, we will compare the proposed energy based
scheme with the AODV against the basic priority with AODV.
5.5.1.1 Network lifetimeThe WSN lifetime has increased because our scheme works on avoiding
dropping packets with high energy usage. This means that, remote nodes from
the sink will not have to retransmit the dropped packets. Because our scheme
avoids dropping packets with high energy consumption during transmission,
network lifetime has increased. Figure 5.3 shows how our proposed scheme
extends the network lifetime. Network lifetime was extended by 3%. As packet
size affects the sending priority, dropping small packets which consumes low
amount of energy, helps in saving network energy.
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Figure 5.3 Network average Energy Level across Network lifetime
5.5.1.2 Energy consumption and delivery ratioFrom Figure 5.4, it is found that the Energy Based Scheme achieves a better
packet delivery ratio value than the Basic Priority Scheduling. Through the
WSN energy consumption, the Energy Based Scheme makes an efficient usage
of the batteries attached to each node in the WSN. It increases the packet
delivery ratio by giving the packets, which consumes more energy, higher
sending priorities. Packets whose energy transmission path level (PEP) is low,
are prioritized with high sending priority. As shown in Figure 5.4, the Basic
Priority Scheduling achieves better delivery ratio at network energy level of
60%. This happens, because of the greedy nature of the propsed scheme.
Sometimes, remote data packets might take the higher priority through its
journey to the destination. This might affect data packets from sink closed
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Basic Piriorty Scheduling Energy Based Scheduling
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nodes. The Energy Based Scheme works on achieving better packet delivery
ratio than the Basic Priority Scheduling. In the Energy Based Scheme, both
control and data packets have the treatment. They get their sending priorities
according to the energy consumption of each one of them.
Figure 5.4 Network Energy consumption vs. Packet Delivery Ratio
The greedy nature of the Energy Based Scheme is considered a normal
behavior. Most of the packets, which consume more energy in transmission, are
remote source packets. This means, that remote data packets have a great
chance to get high sending priority than the other packets. In order to know
how this greedy nature affects the WSN, we measure the fairness of the Energy
Based Scheme and compare it to the fairness of the Basic Priority Scheduling.
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10 20 30 40 50 60 70 80 90 100
Deliv
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Basic Priority Scheduling Energy Based Schema
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5.5.1.3 Fairness IndexFigure 5.5, shows how the Basic Priority Scheduling with AODV
overcomes the proposed scheduling scheme in the fairness. In the Basic Priority
scheme, packets are assigned sending priorities only according to their type.
Assigning priorities to packets according to their types, helps in achieving
better fairness among all the WSN nodes. Sending priorities assigned to packets
from remote nodes are affected by the energy used to deliver the packets, the
energy path level and packet size. Although, these parameters are considered
in priority calculations for each packet, the fairness is affected. The fairness of
the Energy Based Scheme is affected because remote nodes have better chance
to deliver their packets. Besides, there are no weights in calculating the sending
priorities.
5.5.2 Proposed scheme against DSDVEnergy and power management are the main constraints that affects wireless
sensor networks lifetime. These constraints have this sort of importance due to
the nature and effect of WSN. Mainly, most of energy consumption is due to
the packet transmission and reception. In this section, we compare the energy
based scheduling scheme with AODV against the DSDV routing protocol. As,
DSDV is a proactive table driven routing protocol, routing information must be
updated periodically. This leads to overuse of the network energy and a
decrease in its lifetime.
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Figure 5.5 Fairness Index
5.5.2.1 Network lifetimeFigure 5.6 shows how the energy based scheduling scheme increases the
WSN lifetime. It achieves better network lifetime than the DSDV. As, AODV
is a reactive routing protocol (it establishes a route to a destination only on
demand), the energy consumption for transmission and reception is quite less
than in DSDV. Network lifetime was extended by 8%. In addition to that, the
energy based scheduling scheme maintains each operation done for
transmission or reception according to the energy consumption, Packet Energy
Path Level, packet size and deadline.
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0.89
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0.91
0.92
0.93
0.94
0.95
10 20 30 40 50 60 70 80 90 100
Fairn
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Energy Consumption (%)
Basic Priority Scheduling Energy Based Schema
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Figure 5.6 Network average Energy Level across Network lifetime
5.5.2.2 Energy consumption and delivery ratioIn Figure 5.7, we find that the energy based scheduling scheme achieves a
better ratio delivery ratio. Besides, the proposed scheme consumes less energy
during the network lifetime in order to achieve better throughput. Although the
proposed scheme suffers from its greedy nature, which may affect the delivery
ratio, the proactivity nature of the DSDV plays an effective role in the energy
consumption for the goodput packets. The overall packet delivery ratio of our
proposed scheme under the AODV is better than the Basic Priority Scheme
under the DSDV routing protocol.
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40
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60
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80
90
1000 3000 5000 7000 7300 7500
Ener
gy C
onsu
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(%)
seconds
Basic Piriorty Scheduling (DSDV) Energy Based Scheduling
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Figure 5.7 Avearage Network Energy consumption vs. Packet Delivery Ratio in DSDV
5.5.2.3 Fairness IndexAs it is mentioned before, the fairness index is an important factor in
evaluation of any scheduling or routing protocol. In the study, this measure is
used to know the nature of the energy based scheduling scheme against the
DSDV routing protocol. Figure 5.8 shows how the DSDV achieves better and
greater fairness index value than in the proposed scheme. DSDV achieves
better fairness index during the network lifetime, while the energy based
scheduling scheme suffers the fairness problem. This problem is due to the
greedy nature of the proposed scheme. In DSDV, packets of the same type and
nodes, regardless their position or distance from the sink node, are treated by
equally. While in the proposed scheme, there is no equality in packet treatment.
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10 20 30 40 50 60 70 80 90 100
Deliv
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Ratio
(%)
Energy Consumption (%)
Basic Priority Scheduling (DSDV) Energy Based Schema
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Fig. 5.8 Fairness Index of DSDV vs. the AODV with proposed scheme
5.5.3 Proposed scheme against DSRDSR routing protocol is another protocol which is compared with the
proposed scheme with. In practical, the DSR is so closed to the AODV in the
way that forms a route on-demand when a transmitting computer requests one.
However, it uses source routing instead of relying on the routing table at each
intermediate device.
5.5.3.1 Network lifetimeIn Figure 5.9, it is found how the proposed scheme still archives better
overall network lifetime. Network lifetime was extended by 3%. The basic
priority scheduling with the DSR works on assigning equally sending priorities
to control packets then data packets, regardless how much energy is consumed
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10 20 30 40 50 60 70 80 90 100
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Basic Priority Scheduling(DSDV) Energy Based Schema
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by each of them. This way in treatment may lead to dropping high energy
consumption packets or packets from low energy path level.
Figure 5.9: Network average Energy Level across Network lifetime
5.5.3.2 Energy consumption and delivery ratioAs, DSR is an on demand routing protocol, the average energy consumption
for the goodput has lower value than in DSDV. However, the average energy
consumptions for the proposed scheduling scheme is still better than in DSR.
They happen due to the action of the Basic priority scheduling Scheme in DSR.
Packets may face the chance of being dropping, whatever how much energy
they have consumed, or how energy strength is the path that any packet has
used in its journey to the destination. This way in packet treatment leads to an
increase in the average energy consumption for the throughput. Figure 5.10
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1000 3000 5000 7000 7300 7500
Ener
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onsu
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(%)
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Basic Piriorty Scheduling (DSR) Energy Based Scheduling
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shows how the energy based scheduling scheme with AODV still overcomes
the Basic priority scheme with DSR. The proposed scheme still achieves better
overall packet delivery ratio than in DSR. In the Basic priority scheme with
DSR, packets treatment is according to the type only. Control packets might
have better sending position in the buffering queue at each node than the data
packets. While in the energy based scheduling scheme with AODV, packets
whose energy transmission path level (PEP) is low, are prioritized with high
sending priority.
Figure 5.10 Average Network Energy consumption vs. Packet Delivery Ratio in DSR
5.5.3.3 Fairness IndexFigure 5.11 shows how the Basic scheduling scheme with DSR overcomes
the proposed energy based scheduling scheme integrated with AODV in
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95
10 20 30 40 50 60 70 80 90 100
Deliv
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Ratio
(%)
Energy Consumption (%)
Basic Priority Scheduling (DSR) Energy Based Schema
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fairness. Sending nodes, when applying the Basic Priority scheme DSR have a
fair treatment of their packets. However, this fairness in the treatment of
packets, in most cases, may lead to an excessive decrease in the fairness in
index. Some sending nodes might be far from the sink node. Moreover, the
packet energy path level and packet energy consumption during transmission
plays an important role in assigning sending probabilities to each packet in the
queue.
Fig. 5.11 Fairness Index of DSDV vs. the AODV with proposed scheme
5.6 Energy Based Scheduling Scheme with ThresholdFairness is an important factor when applying and comparing any scheme.
Although, the fairness index values does not reflect the level of QoS, which
achieved in the network. However, some WSNs applications might require a
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10 20 30 40 50 60 70 80 90 100
Fair
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high value in fairness index. As, the energy based scheduling scheme suffers a
massive decrease in the fairness when comparing with the Basic Priority
scheduling scheme, a new method in calculating the sending priority for each
packets is used. This way is to use a threshold value.
The threshold is a value used by the Energy Based Scheduling Scheme in
order to increase the fairness index value. Each packet sending priority is
compared to this value. When the PSP exceeds the threshold value, it becomes
equal to 1. Otherwise, the PSP values do not change. Applying this threshold
would help in maximizing the fairness index of the proposed scheme. As,
packets from remote nodes would have the same sending probability like
packets from close nodes.
Figure 5.13 shows how the effect of the distance on the packets dropping
probability. Transmitted packets from remote nodes have lower dropping
probability than other packets from close to sink nodes. Therefore, the
proposed scheduling scheme decreases the fairness index of the entire network.
In order to apply fair treatment to any packets, regardless the location or
nearness of its source, the threshold value should be carefully chosen. The
value of the threshold and how it would be applicable to the used application
could be a future work for the thesis.
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Fig. 5.12 Fairness Index the Energy Based Scheduling Scheme before and afterapplying the threshold
Fig. 5.13 Dropping Probability vs. the distance from the sink node
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5.7 SummaryThis chapter have presented comparisons between the proposed scheduling
energy based schemes integrated with AODV against other the Basic priority
scheduling scheme with DSR and DSDV. These comparisons were according
to network lifetime, amount of energy consumption for the throughput and the
fairness index.
Next, it was shown how to overcome the problem of the fairness. This is
done applying a threshold value to proposed scheduling scheme.
The next chapter will be the conclusion and future works of this research.
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Chapter 6
Conclusion and Future Work
The aim of this research and thesis is to develop a new scheduling scheme for
wireless sensor networks. Through this thesis, we have a brief overview on the
wireless sensor networks architecture, applications, protocols layers and
challenges. After that we discuss the prevouis scheduling scheme and show
how they work. Then, we introduce our proposed energy based scheduling
scheme and show how its integration with the AODV routing protocol. This
scheme has the ability to schedule packets according to their deadlines and
energy consumption. The proposed scheme takes into account the packet
deadlines, size, energy path level and the energy consumption for each packet
during its journey from the source to the sink. After that, a comparison was
done between the proposed energy based scheduling scheme against the basic
priority scheduling scheme.
6.1 ConclusionMany researches have proposed different solutions. These solutions deal
with routing protocols, data packet prioritization, and real-time scheduling.
Most of these solutions prioritize packets at the MAC layer according to their
deadlines and distances to the sink. Packet prioritization by itself cannot
completely support real-time data communication requirements. The scheme
was implemented in NS-2, which is widely used open source software.
In this work, Energy Based Scheduling Scheme with AODV routing
protocol was developed. In this scheme, packets are not only scheduled
according to their deadlines or first in first out. The experimental and
simulation results showed how the proposed scheduling scheme can increase
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the overall network lifetime. Moreover, it can decrease the average energy
consumption for each transmitted packets. Dropping a packet which consumed
high energy during its transmission or a packet arrived from a low energy path
level would lead to a great loss in the overall energy of the network. So, the
proposed scheme works on preventing this behavior by considering the energy
consumption and energy path level in assigning sending probabilities.
However, the fairness index problem rises as a problem for the proposed
scheme. Packets from nodes near to the sink may face the probability of
assigning low sending priorities to them. In order to overcome this problem, we
introduce a threshold idea to be integrated with the proposed scheme. The
threshold works on increasing the fairness index.
The energy based scheduling scheme is integrated with the AODV routing
protocol. It works on the unused bits in the packet headers. Moreover, the
proposed energy based scheduling scheme does not require any support from
the MAC layer.
6.2 Future WorksMany challenges still remain in wireless sensor networks. A lot of research
is ongoing in the field of routing and scheduling. The following could be
considered as future work for this thesis:-
1. Adapting the energy based scheduling scheme to work in WSN with
mobile nodes will be the next step in this research.
2. It would be also an interesting idea if the proposed scheme is
integrated with the other routing protocol such as, Low-energy
adaptive clustering hierarchy.
3. The threshold value and its suitable value for WSN application could
be an interest future work.
4. An idle detection mechanism may be employed such that if an idle
period passes without packet transmission, the head of the queue is
sent immediately.
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5. The proposed scheme could be integrated with the other routing
protocols like Dynamic Source Routing or Destination-Sequenced
Distance Vector routing.
6. An update would be applied on the proposed scheme in order to
overcome the fairness problem.
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Outcome From the thesis
N. E. Mahmoud, M. H. N. Taha, H. N. Elmahdy, and I. A. Saroit, "A SecureEnergy Mechanism for WSN and Its Implementation in NS-2", CiiTInternational Journal of Wireless Communication, vol. 4, issue 16, pp. 984-990, 2012.
M. H. N. Taha , N. E. Mahmoud, H. N. Elmahdy, and I. A. Saroit, "EnergyBased Scheduling Scheme for Wireless Sensor Networks", CiiT InternationalJournal of Wireless Communication, vol. 4, issue 16, pp. 973-975, 2012.
87
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95
Appendix A - Trace File Field Types
The trace format is shown below.
S –t 0.267662078 -Hs 0 -Hd -1 -Ni 0 -Nx 5.00 -Ny 2.00 -Nz 0.00 –Ne -1.000000 -N1
RTR -Nw --- -Ma 0 -Md 0 -Ms 0 -Mt 0 -Is 0.255 -Id -1.255 –It message -Il 32 -If 0 -Ii 0
-Iv 32
r –t 100.004776054 -Hs 0 -Hd -1 -Ni 1 -Nx 25.05 -Ny 20.05 -Nz 0.00 –Ne -1.000000 -
N1 AGT -Nw --- -Ma a2 -Md 1 -Ms 0 -Mt 800 -Is 0.0 -Id -1.0 –It tcp -Il 1020 -If 2 -Ii 21
-Iv 32 -Pn tcp -Ps 0 -Pa 0 -Pf 1 -Po 0
Field 0: event type s: send
r: receive
d: drop
f: forward
Filed 1: General tag -t: time
Field 2: Next hop info -Hs: id for this node
-Hd: id for next hop towards the destination
Field 3: Node property type tag -Ni: node id
-Nx –Ny -Nz: node’s x/y/z coordinate
-Ne: node energy level
-Nl: trace level, such as AGT, RTR, MAC
96
-Nw: reason for the event
Field 4: packet info at MAC level -Ma: duration
-Md: dest’s ethernet address
-Ms: src’s ethernet address
-Mt: ethernet type
Field 5: Packet information at IP level -Is: source address. Source port number
-Id: dest address.dest port number
-It: packet type
-Il: packet size
-If: flow id
-Ii: unique id
-Iv: ttl value
Field 6: Packet info at “Application level”which consists of the type of application like ARP, TCP, CBR, the type of ad-hoc
routing protocol like DSDV, DSR, AODV etc. The field consists of a leading –P and the
list of tags for different applications. For values of the fields for AODV and CBR are
described below;
For AODV :
-Pt : Control message type,
-Ph: Hop-count,
-Pb: Broadcast-id,
-Pd: Destination,
-Pds: Dest Seqno,
-Ps: Source,
-Pss: Source Seqno
97
-Pl: Lifetime.
-Pc: Pkt Type, REPLY/ERROR
For CBR :
-Pn: This denotes the application of “CBR”
-Pi: sequence number
-Pf: how many times this pkt was forwarded
-Po: optimal number of forwards
98
Appendix B - SAMPLE AWK SCRIPTS
# Lim Kwang Yong
# Usage: awk -f <awk_script.awk> <trace_file.tr>
# Parse a ns2 wireless trace file and generate performance metrics
BEGIN {
droppedRTGpackets=0;
droppedbRTGbytes=0;
droppedMACbytes=0;
droppedMACpackets=0;
droppedbDATAbytes=0;
droppedbDATApackets=0;
droppedIFQpackets=0;
droppedLQIbytes=0;
droppedLQIpackets=0;
droppedIFQbytes=0;
totalDROPPEDpackets=0;
totalDROPPEDbytes=0;
dataSent=0;
dataRecd=0;
sentData=0;
sentDataBytes=0;
TotalsentData=0;
TotalsentDataBytes=0;
recdData=0;
recdDataBytes=0;
sends=0;
recvs=0;
RTGbytes=0;
fwdData=0;
99
fwdDataBytes=0;
fwdRtg=0;
fwdRtgBytes=0;
fwdMac=0;
fwdMacBytes=0;
highest_packet_id=0; #used to compare with the packet id
highest_time=0
sum=0;
RTG=0;
MACDATA=0;
MACRTG=0;
}
{
#=============================
# Check for the highest packet ID & time
#=============================
action = $1;
time = $2;
node_id = $3
if ($7 =="cbr"){packet_id = $6;};
if ( packet_id > highest_packet_id ) {highest_packet_id = packet_id;};
if ( time > highest_time) {highest_time = time}
#============
# Calculate delay
#============
if ( start_time[packet_id] == 0 ) {start_time[packet_id] = time;};
if ( action != "D" ) {
if ( action == "r" ) {end_time[packet_id] = time;};
}
else {end_time[packet_id] = -1;};
100
#===========
#Calculate PDF
#===========
if (($1 == "s") && ($7 == "cbr") && ($4 =="AGT")) {
sends++;
dataSent=dataSent+$8;
}
if ( ( $1 == "r") && ( $7 == "cbr" ) && ( $4 == "AGT" ) ) {
recvs++;
dataRecd=dataRecd+$8;
}
#===============
# Calculate RTG load
#===============
if ((( $1 == "s") || ($1=="f") ) && ( $7 == "cbr" ) && ( $4 =="RTR" )) {
sentData++;
sentDataBytes=sentDataBytes+$8;
}
if ( ( $1 == "r") && ( $7 == "cbr" ) && ( $4 == "RTR" ) ) {
recdData++;
recdDataBytes=recdDataBytes+$8;
}
#==============
# RTG protocol pkts
#==============
if ( (($1=="f") || ($1=="s") ) && ($4 == "RTR") && ($7 =="AODV" ) ) {
RTG++;
RTGbytes=RTGbytes+$8;
}
#============
# MAC data pkts
101
#============
if ( (($1=="f") || ($1=="s") ) && ($4 == "MAC") && ($7 =="cbr" ) ) {
MACDATA++;
}
#=============
# MAC RTG pkts
#=============
if ( (($1=="f") || ($1=="s") ) && ($4 == "MAC") && ($7 =="AODV" ) ) {
MACRTG++;
}
#==============
# Dropped data pkts
#==============
if ( ($1 == "D") && ($7 =="cbr") && ( $4 == "RTR" )){
droppedDATAbytes=droppedDATAbytes+$8 ;
droppedDATApackets=droppedDATApackets+1;
}
#===============
# Dropped MAC pkts
#===============
if ( ($1 == "D") && ($4 == "MAC" )){
droppedMACbytes=droppedMACbytes+$8 ;
droppedMACpackets=droppedMACpackets+1;
}
#===============
# Dropped RTG pkts
#===============
if ( ($1 == "D") && ($4 == "RTR" ) && ($8 == "AODV")){
droppedRTGbytes=droppedRTGbytes+$8 ;
droppedRTGpackets=droppedRTGpackets+1;
}
102
#==============
# Dropped IFQ pkts
#==============
if (($1 == "D") && ($4 == "IFQ")){
droppedIFQbytes=droppedIFQbytes+$8 ;
droppedIFQpackets=droppedIFQpackets+1;
}
#==============
# Dropped LQI pkts
#==============
if (($1 == "D") && ($4 == "IFQ")){
droppedLQIbytes=droppedLQIbytes+$8 ;
droppedLQIpackets=droppedLQIpackets+1;
}
#==============
# Total dropped pkts
#==============
if ($1 == "D") {
totalDROPPEDpackets++;
totalDROPPEDbytes=totalDROPPEDbytes+$8
}
#==============
# Forward data pkts
#==============
if ( ($1 == "f") && ($7 == "cbr") && ($4 == "RTR" ) ) {
fwdData++;
fwdDataBytes=fwdDataBytes+$8;
}
#==============
# Forward RTG pkts
#==============
103
if ( ( $1 == "f") && ($7 == "AODV") && ($4 == "RTR") ) {
fwdRtg++;
fwdRtgBytes=fwdRtgBytes+$8;
}
#===============
# Forward MAC pkts
#===============
if ( ( $1 == "f") && ($4 == "MAC" ) ) {
fwdMac++;
fwdMacBytes=fwdMacBytes+$8;
}
#==============
# Total forward pkts
#==============
if ( $1 == "f") {
fwdpackets++;
fwdBytes=fwdBytes+$8;
}
if ($1 == "D") {
droppingnodes= $3;
}
}
END {
for ( packet_id = 0; packet_id <= highest_packet_id; packet_id++ ) {
start = start_time[packet_id];
end = end_time[packet_id];
packet_duration = end - start;
if (start < end) sum= packet_duration+sum;
}
#==========
# Show results
104
#==========
printf("\n .......Data parsed from trace file with 25
NODES.............\n\n") >> "performance.txt";
printf(" 1. No. of CBR Packets sent = %d PACKETS \n ", sends) >>
"performance.txt";
printf(" 2. No. of CBR Bytes sent = %d BYTES \n", dataSent) >>
"performance.txt";
printf(" 3. No. of CBR Packets received = %d PACKETS \n", recvs) >>
"performance.txt";
printf(" 4. No. of CBR Bytes received = %d BYTES \n", dataRecd) >>
"performance.txt";
printf(" \n .......Routing details.............\n\n") >>
"performance.txt";
printf(" 5. No. of routing packets = %d PACKETS \n",RTG) >>
"performance.txt";
printf(" 6. No. of routing bytes = %d BYTES \n",RTGbytes) >>
"performance.txt";
printf(" \n .......MAC details.............\n\n") >> "performance.txt";
printf(" 7. No. of MAC packets for data sent = %d PACKETS \n", MACDATA)
>> "performance.txt";
printf(" 8. No. of MAC packets for Rtg sent = %d PACKETS \n", MACRTG) >>
"performance.txt";
printf(" 9. Total No. of MAC Packets sent = %d PACKETS \n",
MACRTG+MACDATA) >> "performance.txt";
printf(" \n .......Forwarding details............\n\n") >>
"performance.txt";
printf(" 10. No. of DATA Packets Fwd = %d PACKETS \n", fwdData) >>
"performance.txt";
printf(" 11. No. of DATA Bytes Fwd = %d BYTES \n", fwddataBytes) >>
"performance.txt";
printf(" 12. No. of RTG Packets Fwd = %d PACKETS \n", fwdRtg) >>
105
"performance.txt";
printf(" 13. No. of RTG Bytes Fwd = %d BYTES \n", fwdRtgBytes) >>
"performance.txt";
printf(" 14. No. of MAC Packets Fwd = %d PACKETS \n", fwdMac) >>
"performance.txt";
printf(" 15. No. of MAC Bytes Fwd = %d BYTES \n", fwdMacBytes) >>
"performance.txt";
printf(" 16. Total No. of Fwd packets = %d PACKETS \n", fwdpackets) >>
"performance.txt";
printf(" 17. Total No. of Fwd Bytes = %d BYTES \n", fwdBytes) >>
"performance.txt";
printf(" \n ........Dropping details............\n\n") >>
"performance.txt";
printf(" 18. Dropping nodes are %d nodes \n", droppingnodes) >>
"performance.txt";
printf(" 19. No. of dropped data (packets) = %d PACKETS
\n",droppedDATApackets) >> "performance.txt";
printf(" 20. No. of dropped data (bytes) = %d BYTES \n",droppedDATAbytes)
>> "performance.txt";
printf(" 21. No. of dropped MAC (packets) = %d PACKETS
\n",droppedMACpackets) >> "performance.txt";
printf(" 22. No. of dropped MAC (bytes) = %d BYTES \n",droppedMACAbytes)
>> "performance.txt";
printf(" 23. No. of dropped RTG (packets) = %d PACKETS
\n",droppedRTGpackets) >> "performance.txt";
printf(" 24. No. of dropped RTG (bytes) = %d BYTES \n",droppedRTGbytes)
>> "performance.txt";
printf(" 25. No. of dropped IFQ (Packets) = %d PACKETS
\n",droppedIFQpackets) >> "performance.txt";
printf(" 26. No. of dropped IFQ (bytes) = %d BYTES \n",droppedIFQbytes)
>> "performance.txt";
106
printf(" 27. No. of dropped LQI (Packets) = %d PACKETS
\n",droppedLQIpackets) >> "performance.txt";
printf(" 28. No. of dropped LQI (bytes) = %d BYTES \n",droppedIFQbytes)
>> "performance.txt";
printf(" 29. Total No. of Dropped (packets) = %d PACKETS
\n\n",totalDROPPEDpackets) >> "performance.txt";
printf(" 30. Total No. of Dropped (Bytes)) = %d BYTES
\n\n",totalDROPPEDbytes) >> "performance.txt";
printf("\n .............PERFORMANCE METRICES .....................\n\n")
>> "performance.txt";
printf(" 1. Packet Delivery Ratio (PDR %) = %f %\n", (recvs/sends)*100)
>> "performance.txt";
printf(" 2. Average Network delay = %f \n", sum/highest_packet_id) >>
"performance.txt";
printf(" 3. Network Throughput = %f \n", (dataRecd/highest_time)/25) >>
"performance.txt";
printf(" 4. Normalised routing load (Packets %) = %f %\n",
(RTG/sentData)*100) >> "performance.txt";
printf(" 5. Normalised routing load (Bytes %) = %f %\n",
(RTGbytes/sentDataBytes)*100) >> "performance.txt";
printf(" 6. Routing OVERHEAD (Packets %) = %f %\n",
(MACRTG/MACDATA)*100)
>> "performance.txt";
printf(" 7. Optimal Hop Count = %f \n\n", MACDATA/sends) >>
"performance.txt";
صـــالملخ
(كموووقكط وووتشكار تلوووكتةكا تووواكموووتاكتشتمكلوووتكمكتط وووت ك تت ووو كWSNsتتكوووشبكاوووالكتشكار تلوووكتةكا ووو ك ك
تكتالوووذكهوووالكا تكطش شم وووتكمل ووو ككا ووو ك كارت وووترشهوووالكا ط وووتشكار تلوووكتةم كبالك ووولتكا وووالك كموووقك ووو ك
ا كسوووكذم ك ا ك وووو ك ا وووطتي ك ا سط وووو ك ووواكا كسمووووسكمووووقك جووووترشكا رطلوووتك ووووشثكتةوووسعك ووووشة ك ا وووك ك وووواك
تطوو كا تطال ووتشكمووتاكطلووذكا ط ووتشكار تلووكتةم ك بكا ةتموو ككا وواكت طوو فكمسووال كه وونكاطوو ك ووشةكطلووذكهووالكا ط ووتشك
كبلك كمست ك اكاالك كارت ترشكا ك طفسلتكمجبكابكتت تعكبت سة كي ىكتطظ اك
جس وووو كهوووولبكط وووو كا ال تطووووتشك وووواكا ش وووو كا ة ووووا كه وووونكتك وووو كهووووالكا ووووسك مووووك كم ططووووتشكمسمووووس كك
ا ططوووتشكي ووواكتةسموووسكل شموووتشكا ةووولبك وووتك شاي وووسهتكطلت ووو كابككيطوووتدكا شمووو ك ةووولبكركم كوووقكلبكتوووسياك
ووواكفوووذ ثكا وووشفكي ووواكا لوووالك رك وووسكمووو كاطتظوووتةككي وووذكا لوووالك كي وووىكمةوووت تطال وووتشكا ووولمقكا ة ووواكل ك
ابكك ووو تشكا ةلمووو كمووو كك وووىك وووسابكا طت ووو كه ووونكاطووو ككا كاتا تلوووت ا ةووولبك ككتوووت ذكا ةووولبك ووواكووووفشثكششم ووو
كةلم ك سكا تل ك كشت كيت كمقكلم كتس لتكك ىك ملتلت ا مقكا كقكابكتكشبك
ابكا تطووشمذكا سووت ذكمووقكاموو كا ت وو ك وواكهجوواك كتك فوو كا ط ووتشكار تلووكتةم ك ووسك ووتيسك وواكتمووت كاربةووتعكك
ي ووواكا ةفوووتفكي ووواكا طت ووو ك كتموووت ككاربةوووتعكا ةت ووو ك ووواكمجووترشكا تشم ووو ك كا ت طووو فككتذكووولك وواكهوووااكا جوووت
ك تك وووو كهووووالكا بةووووتعكي وووواكايطووووتدك تب وووو كر ووووت كتركيووووس ككال ووووذكمووووقكا ط ووووتشكار تلووووكتة كي ووووذكا لووووالك
اهوووسكملوووك كا طت ووو كا كت ووو كمشاملووو كةوووشعكمجوووبكتكطووواكا لوووالك كا وووسة كي ووواك بتإلموووت كك وووىكن ووو ك وووتبكهوووالكا ال
مووووتاكطلووووذكاووووالكتشكا تلووووكتةك ج ووووعكا ك شمووووتشك تة لووووتكره ووووت ك ةوووووسكل كتتالووووعكهتووووىككا ط ووووتشكار تلووووكتةم
كا ظشاهذك اكا ش كا ة ا
وووواكاووووالكتشكار تلووووكتةكا وووو ك ك ووووتبكا ةوووولبكا ذ وووو كمووووتاك مووووكلتك وووواك ت وووو كارطتظووووتةك وووواكا ط ووووتشك
مووتاكتك وو قكا شمووتشكك ووىكا ةوولبك ووتك كهلموو كه وونكتك وو ككوو كط طوو كي وواكتك وو قكا شمووتشكك ووىككووا ش وو ط ك
هوووااكا ووو شرك ووواكتةسموووسكا شموووتشكا ةلمووو كركمو ووواكبكووو قكاريتالوووتةك وووشادك ووواكي وووذكك شاي وووسكطلت ووو ك لوووت
ووواكا وووىكمتطوووبكن ووو ك دطووو ك وووسكمووو كك وووىكك ووو تشكا ةووولبكيت ووو كار وووت سابك طت ووو ككا لوووالك كل كا وووتل قكا طت ووو
الوووذكا ك وووذكار تذامووواك لوووالكتشكار تلوووكتةكا ووو ك كك ووو كهذمووو ك شتمووو كل طوووتدكا كسموووسكموووقكا تطال وووتش ك مكت
ككيسا كا لالك
جس وو كك وواكهووااكا طووفكمووتاك م طووفك جس وو كمسوو اكم طووفكا طت وو كا كم تووذ كمووتاكت ووسما وواكهووااكا الةوونك
تةسموووسكا شمووو كارة وووت ك ةووولبك ووو اك وووفك وووتك شاي وووسكا طلت ووو ك ك كوووقكام وووتك وووتك وووالك ك ت وووتشكا طت ووو ك
ا توووذ كا طووفككم ووشبك كه وونAODVا تووو كبت لووالك ك ك ووسكتوواك مووطكهووااكا طووفكمووعكبذ تشكووش كا تشم وو ك
م طوووفكا جس ووو ككي ووواكا وووت سابكا تطوووتشكخ وووذكا سوووت سم ك ووواكا ةلمووو كموووقك ووو كهوووااكا الةووون كتوووتاكم تةطووو
ك ووووذك كتووووتاكا تةطووووتشك ووووتكNS-2 ن وووو كبت ووووت سابككا تذهوووو كمووووعكم طووووفكا جس وووو كا ت وووو كناشكا شموووو
ابكا طتوووت طكت الووو كلبكم طوووفكا طت ووو كا جس ووو كا ت ووو كمك ووو كي ووواككا لوووالك ك ا وووتل قكا طت ووو ك كم اوووذكا طلاهووو
كل ذى كك تبكم اذكا كسا كمتت ذك الت كتمت كه ت كا لالك ك ت كا تل قكا طت ك ةلب كمقكطته
مذموووعكك96م ةووو ك كم ةووو كبوووت الذامطك ك ت ووو كبوووت ذامعكتت ووو قكك2 كتت ووو قكا ذ وووت ك وووت كابوووشارك كيوووس ك
ك- كطشة ك تكم اكم صك لالكاربشار:
ا التركار :كم سم
كاربشاركا تت ك اكا ذ ت قكهااكا التركاذ ك لك ك كيذضكم صك كمت
ا تطا:كاالكتشكار تلكتةكا ك ا الترك
كمووتكمتك وو كبلووتكمووقكه تكوو ك ك كمت وو قكهووااكا الووتركاووذ كتف وو اك لووالكتشكار تلووكتةكا وو ك ك
كتطال تشك كتةسمتش كك تكتةتش كي اكاذ ك الذ تشكشرشكا تشم
ا التركا ت ن:كم كتط لم تشكا جس ك اكاالكتشكار تلكتةكا ك
كاذهتكتف تك ططتشكا جس ك اكاالكتشكار تلكتةكا ك كمت قكهااكا الترك
ا طت ي اككمكت سك جس كا التركا ذابع:كم طفكم تذ
ك كمت قكهااكا التركيذمتك كاذهتكتف تك طفكا جس كا تذ
ا ةتكت ك كا طتت طا التركا تما:ك
ك كمت قكهااكا التركيذمتك كاذهتكتف تكك طتت ط
ا ست س:كا و ك كا ك كا ست ال اا الترك
كهااكا التركيذمتكتف تك و ك كا ك كا ست ال اك ذ ت كمت قك
رةــــــــــة القاھـــــــــــجامعكلیة الحاسبات و المعلومات
اتـــقسم تكنولوجیا المعلوم
الالسلكیةاإلستشعارشبكاتعبرالبیاناتتناقلجودةتحسین
إعداد
طھالدیننصرحامدمحمد
والمعلوماتالحاسباتكلیةإلىمقدمةرسالة
القاھرةجامعة
الدكتوراهدرجةعلىالحصولمتطلباتمنكجزء
المعلوماتتكنولوجیافي
تحت إشراف
أ.د ھشام نبیھ المھديأستاذ بقسم تكنولوجیا المعلومات
كلیة الحاسبات والمعلوماتجامعة القاھرة
أ.د إیمان علي ثروت إسماعیلوكیل الكلیة لشئون التعلیم والطالب
كلیة الحاسبات والمعلوماتجامعة القاھرة
یونیو2013
